INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING | Year:2017 | دوره:13 |Papers Count:119

SELECTING THE PROPER ACQUISITION STRATEGY FOR NEEDED TECHNOLOGIES, IS ONE OF THE KEY STRATEGIC DECISIONS IN FORMULATING TECHNOLOGY STRATEGY FOR A COMPANY. THERE ARE A NUMBER OF FACTORS WERE FOUND TO BE INFLUENTIAL IN THE SELECTION OF TECHNOLOGY ACQUISITION STRATEGY. THIS PAPER DEALS WITH SELECTING TECHNOLOGY ACQUISITION STRATEGY AS A MULTIPLE CRITERIA DECISION MAKING (MCDM) PROBLEM. THE PROPOSED SOLUTION TO THE PROBLEM IN THIS PAPER IS THE PROMETHEE METHOD. IN THIS PAPER, AFTER DEPICTING TECHNOLOGY TREE FOR A GIVEN PRODUCT AND SELECTING A STRATEGIC TECHNOLOGY UNIT (STU), PROMETHEE METHOD WAS EMPLOYED FOR SELECTING THE BEST STRATEGY FOR ACQUIRING REQUIRED TECHNOLOGY BASED ON SEVERAL CRITERIA SUCH AS: COST, TIME, LEARNING, CURRENT CAPABILITY AND COMPETITIVE ADVANTAGE. A CASE OF AN INDUSTRIAL AUTOMATION EQUIPMENT MANUFACTURER NAMED GESHM VOLTAGE IS PRESENTED FOR THE ILLUSTRATION OF THE OUR PROPOSED APPROACH. THE PROPOSED APPROACH IS EXPECTED TO EFFECTIVELY HELP DECISION MAKING ON WHICH STRATEGY IS ADOPTED FOR ACQUISITION OF REQUIRED TECHNOLOGIES.

CONDITION-BASED MAINTENANCE (CBM) MODELLED THROUGH PROPORTIONAL HAZARDS MODEL (PHM) IS A KIND OF MAINTENANCE STRATEGY IN WHICH A SYSTEM IS INSPECTED IN INTERVALS OF TIME AND THE OPTIMAL REPLACEMENT POLICY IS DETERMINED BASED ON AN OPTIMAL THRESHOLD VALUE CALLED CONTROL LIMIT. IN THIS PAPER, A MODEL IS PRESENTED TO DETERMINE A CONTROL LIMIT FOR REDUNDANT SYSTEMS AS WHOLE SYSTEMS IN WHICH THEIR COMPONENTS WOULD BE REPLACED UNDER THE CONTROL LIMIT POLICY FOR THE WHOLE SYSTEM. IN REDUNDANT SYSTEMS, DURING EACH INSPECTION TIME, A SYSTEM FAILURE IS OCCURRED LESS SINGLE-UNIT SYSTEMS. THE PROPOSED APPROACH IS DEMONSTRATED THROUGH AN EXAMPLE OF REDUNDANT SYSTEMS.

IN TODAY'S WORLD, NATURAL DISASTERS SUCH AS EARTHQUAKES, FLOODS, CRISES SUCH AS TERRORIST ATTACKS AND PROTESTS THREATEN THE LIVES OF MANY PEOPLE. HENCE, IN THIS RESEARCH WE PRESENT A MATHEMATICAL MODELING THAT PROVIDE EFFICIENT AND EFFECTIVE MODEL TO LOCATE TEMPORARY DEPOT, EQUITABLE DISTRIBUTION OF RESOURCES AND MOVEMENT OF INJURED PEOPLE TO HEALTH CENTERS, WITH THE AIM OF DEVELOPING THE MULTI-OBJECTIVE MODEL AND CONSIDERING MULTIPLE CENTRAL DEPOT, MULTIPLE TEMPORARY DEPOT AND SEVERAL TYPE OF RELIEF ITEMS IN THE MODEL. THIS PAPER IS CONSIDERED CERTAINTY STATE AND UNCERTAINTY OF INFLUENCING PARAMETERS OF THE MODELS IN ROBUST OPTIMIZATION FOR THREE DIFFERENT LEVELS UNCERTAINTY AND IN DIFFERENT SIZE WITH CONSIDERATION OF TRADITIONAL GOALS FUNCTION AND HUMANITARIAN PURPOSES FUNCTIONS SIMULTANEOUSLY. THE MODEL HAS BEEN SOLVED WITH MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION ALGORITHM (MOPSO) AND GAMS SOFTWARE TO VALIDATE THE MODEL. SOME NUMERICAL EXAMPLES ARE PRESENTED. IN ADDITION, WE PRESENT SENSITIVITY ANALYZES OF MODEL AND STUDY THE RELATIONSHIP OF THE NUMBER OF TEMPORARY DEPOT LOCATION AND THE NUMBER OF INJURED PEOPLE TO MOVE TO HEALTH CENTERS AND THE NUMBER OF UNCOVERED DAMAGED POINTS.

THIS STUDY CONSIDERS PRICING, PRODUCTION AND TRANSPORTATION DECISIONS IN A STACKELBERG GAME BETWEEN THREE-STAGE, MULTI-PRODUCT, MULTI-SOURCE AND SINGLE-PERIOD SUPPLY CHAINS CALLED LEADER AND FOLLOWER. THESE CHAINS CONSIST OF; MANUFACTURERS, DISTRIBUTION CENTERS (DCS) AND RETAILERS. COMPETITION TYPE IS HORIZONTAL AND SC VS. SC. THE RETAILERS IN TWO CHAINS TRY TO MAXIMIZE THEIR PROFIT THROUGH THE PRICING OF PRODUCTS IN DIFFERENT MARKETS AND REGARDING THE TRANSPORTATION AND PRODUCTION COSTS. A BILEVEL NONLINEAR PROGRAMMING MODEL IS FORMULATED IN ORDER TO REPRESENT THE STACKELBERG GAME. PRICING DECISIONS ARE BASED ON DISCRIMINATION PRICING RULES, WHERE WE CAN PUT DIFFERENT PRICES IN DIFFERENT MARKETS. AFTER THAT THE MODEL IS REDUCED TO A SINGLE-LEVEL NONLINEAR PROGRAMMING MODEL BY REPLACING KARUSH-KUHN-TUCKER CONDITIONS FOR THE LOWER LEVEL (FOLLOWER) PROBLEM. FINALLY, A NUMERICAL EXAMPLE IS SOLVED IN ORDER TO ANALYZE THE SENSITIVITY OF EFFECTIVE PARAMETERS.

DUE TO INCREASE THE IMPORTANCE OF ENVIRONMENTAL ISSUES, NOWADAYS, VARIOUS FACTORIES NOT ONLY HAVE TO PROVIDE THE CUSTOMERS’ NEEDS BUT HAVE TO CREATE A CYCLE FOR RETURNED PRODUCTS IN ORDER TO RECYCLE, DISPOSE OR REMANUFACTURE THEM. IN THIS PAPER, A STUDY WAS CONDUCTED TO PROVIDE A MODEL FOR REVERSE SUPPLY CHAIN. AT FIRST, AN INTRODUCTION ABOUT THE IMPORTANCE OF THE REVERSE LOGISTICS SUPPLY CHAIN IS EXPRESSED AND THEN REVERSE SUPPLY CHAIN MODEL WHICH INCLUDES CUSTOMER ZONES, COLLECTION CENTERS, REMANUFACTURING CENTERS, DISASSEMBLY CENTERS, RECYCLING CENTERS, PRIMARY MARKETS, AND SECONDARY MARKET DELIVERED. THE PROBLEM CONSIDERED IN THIS RESEARCH INVOLVES DECISIONS REGARDING THE NUMBER AND LOCATION OF DIFFERENT FACILITIES TO BE ESTABLISHED IN THE NETWORK AND THE RATE OF FLOW OF DIFFERENT PRODUCTS, COMPONENTS AND MATERIALS BETWEEN EACH STAGE OF THE REVERSE SUPPLY CHAIN. THIS PROBLEM SOLVED WITH EXACT SOLUTION IN THIS PAPER AND THE RESULT PRESENTED AT THE END OF PAPER.

A MULTI-PERIODIC, MULTI-ECHELON GREEN SUPPLY CHAIN NETWORK CONSISTING OF MANUFACTURING PLANTS, POTENTIAL DISTRIBUTION CENTERS, AND CUSTOMERS IS DEVELOPED IN THIS RESEARCH. THE PROBLEM HAS THREE OBJECTIVES INCLUDING MINIMIZATION OF THE TOTAL COSTS OF THE GREEN SUPPLY CHAIN NETWORK, MAXIMIZATION OF THE AVERAGE SAFE INVENTORY LEVELS OF THE MANUFACTURING PLANTS AND THE DISTRIBUTION CENTERS AND MINIMIZATION OF THE ENVIRONMENTAL IMPACTS OF THE MANUFACTURING PLANTS IN PRODUCING, HOLDING AND DISPATCHING THE PRODUCTS AND ALSO THE ENVIRONMENTAL IMPACTS OF THE DISTRIBUTION CENTERS IN HOLDING AND DISPATCHING THE PRODUCTS. THE PROBLEM IS FIRST FORMULATED AS A MIXED-INTEGER MATHEMATICAL MODEL. THEN, TO SOLVE THE PROBLEM, ONE MULTI-OBJECTIVE DECISION-MAKING (MODM) METHOD CALLED THE AUGMENTED WEIGHTED TCHEBYCHEFF METHOD IS EMPLOYED AS A SOLUTION METHOD TO SOLVE THE PROPOSED MATHEMATICAL MODEL. AT THE END, USING A NUMERICAL EXAMPLE, THE PERFORMANCE OF THE PROPOSED SOLUTION METHOD IS ANALYZED.

THE MAIN SCHEDULING PROBLEMS IN THE LITERATURE HAVE FOCUSED ON ANALYZING THE PROBLEM OF ORGANIZING MACHINES AND PRODUCTION CAPABILITIES IN AN ENVIRONMENT WITH FIXED SELLING PRICE. HOWEVER, IN A MAKE-TO-ORDER (MTO) ENVIRONMENT THE ASSUMPTION OF PRICING CAN BE FOLLOWED IN AN INTERFACE WITH SCHEDULING PROBLEM. IN THIS RESEARCH WE FIRST REVIEW THE EXISTENCE LITERATURE OF ORDER ACCEPTANCE AND SCHEDULING IN PARTICULAR IN A MTO ENVIRONMENT. USING AN OASP PROBLEM, THE ORDERS ARE CALCULATED BY THEIR CONTROLLABLE PROCESSING TIME, DUE DATE, DEADLINE, RELEASE DATE AND SEQUENCE DEPENDENT SETUP TIME. THEN UNDER JOINT OPTIMIZATION APPROACH, THE PRICING DECISIONS SET FOR UNRELATED PARALLEL MACHINE ENVIRONMENT. THE OBJECTIVE OF THE PROBLEM IS TO MAXIMIZE THE TOTAL NET PROFIT. THE RESULTS SHOW THAT THE BASIC DEVELOPED PROBLEM CAN SOLVE THE SCHEDULING DECISIONS BASED ON DIFFERENT LEVELS OF PRODUCTS’ PRICED. THUS THE PROBLEM SOLVES THESE TWO CATEGORIES OF DECISIONS SIMULTANEOUSLY.

WITH THE INCREASING EMPHASIS ON SUPPLY CHAIN NETWORK DESIGN (SCND) VULNERABILITIES, EFFECTIVE MATHEMATICAL TOOLS FOR ANALYZING AND UNDERSTANDING APPROPRIATE SUPPLY CHAIN BY RISK MANAGEMENT ARE NOW ATTRACTING MUCH ATTENTION. THE AIM OF THIS PAPER IS GENERATED A ROBUST CLOSED-LOOP SUPPLY CHAIN NETWORK WITH THE METAHEURISTIC AND EXACT SOLUTION PLANNING. MOREOVER, THE DOWNSIDE RISK IS INCORPORATED INTO THE OBJECTIVE FUNCTIONS OF THE TWO-STAGE STOCHASTIC PROGRAMMING MODEL AS A RISK MEASURE. HENCE, THE DEVELOPED STOCHASTIC MODEL AIMS TO MINIMIZE THE EXPECTED TOTAL COST AND THE DOWNSIDE RISK, SIMULTANEOUSLY. IN ORDER TO ADDRESS THE PROBLEM, RED DEER ALGORITHM (RDA) AS ONE OF THE POWERFUL RECENT ALGORITHMS AND GENETIC ALGORITHM (GA) AS A WELL-KNOWN METAHEURISTIC ARE UTILIZED IN THIS STUDY. IN ADDITION, THE PARAMETERS OF ALGORITHMS ARE TUNED BY RESPONSE SURFACE METHOD (RSM) WITH AN MODM APPROACH TO ESTIMATE THE PROPER VALUES OF THE PARAMETERS FOR PRESENTED METAHEURISTIC ALGORITHMS TO IMPROVE THEIR PERFORMANCE. TO EXPLAIN THE EFFICIENCY AND EFFECTIVENESS OF METHODS, FOUR METRICS ARE INTRODUCED. AT THE END, THE RESULTS SHOW THAT THE ICA ACHIEVES THE BETTER SOLUTION THROUGH THE MOST OF TESTS PROBLEM.

PROMOTION OF QUALITY MANAGEMENT SYSTEM IN ROAD MAINTENANCE AND TRANSIT ORGANIZATIONS TO DEVELOP REGIONAL AND INTERNATIONAL COOPERATION IS INEVITABLE. ONE OF THE BEST SOLUTIONS FOR PROMOTION OF QUALITY MANAGEMENT SYSTEM IS ACHIEVING THE HIGHEST POSSIBLE DEGREE OF ADAPTABILITY TO LEAN MANUFACTURING APPROACH. THE BASIC LEAN MANUFACTURING ELEMENTS INCLUDE PRODUCTION FLOW, ORGANIZING, PROCESS CONTROL, MEASUREMENT AND SUPPORTING. MEASUREMENT IN LEAN MANUFACTURING REFERS TO SYSTEM LEANNESS, SO ROAD MAINTENANCE AND TRANSIT ORGANIZATIONS SHOULD CONSTANTLY ASSESS THE DEGREE OF ADAPTABILITY OF THEIR QUALITY MANAGEMENT SYSTEMS TO LEAN MANUFACTURING CRITERIA. IN THIS STUDY, WE PROVIDE AN IMPROVED FUZZY MODEL FOR DETERMINING LEANNESS OF QUALITY MANAGEMENT SYSTEMS IN ROAD MAINTENANCE AND TRANSIT ORGANIZATIONS. IN THE MENTIONED FUZZY IMPROVED METHOD, WEIGHTED VALUE OF EXPERTS CAN BE IN FORM OF TRIANGULAR FUZZY NUMBERS AND THE NUMBER OF JUDGING EXPERTS FROM ONE CRITERION TO ANOTHER CAN BE VARIABLE. THE CASE STUDY OF THIS RESEARCH IS RELEVANT TO QUALITY MANAGEMENT SYSTEM IN ROAD MAINTENANCE AND TRANSIT ORGANIZATION'S ARDABIL PROVINCE IN IRAN. THE RESULTS INDICATE SUM SQUARE ERROR BETWEEN THE FUZZY PROPOSED MODEL AND THE KNOWN TECHNIQUE OF WILLIS METHOD IS EQUAL TO 0.08 WHICH SHOWS SIGNIFICANT DIFFERENCES BETWEEN FUZZY PROPOSED MODEL AND WILLIS TECHNIQUE. THIS PROBLEM SHOWS THE ACCURACY, RELIABILITY, EFFICIENCY AND CERTITUDE OF THE FUZZY PROPOSED MODEL IN DETERMINING THE RATE OF LEANNESS IN A SYSTEM.

IN SOMEPROCESSES THE QUALITY CHARACTERISTIC IS CHARACTERIZED BY A FUNCTIONAL RELATIONSHIP BETWEEN A RESPONSE VARIABLE AND PREDICTOR VARIABLES WHICH IS NAMED AS PROFILE. THE RESPONSE VARIABLE IN PROFILESUSUALLYFOLLOWS NORMAL DISTRIBUTION. HOWEVER, SOMETIMES THE RESPONSE VARIABLES HAVE DIFFERENT DISTRIBUTIONSSUCH AS BERNOULLI OR BINOMIAL. ON THE OTHER HAND, IN MANY SITUATIONS IN REAL APPLICATIONS THE IN-CONTROL (IC) PARAMETERS OF THE PROCESSES ARE NOT KNOWN A PRIORI AND ALSO THERE ARE NO SUFFICIENT SAMPLES TO EXECUTE PHASE I ANALYSISTO ESTIMATE THE IN-CONTROL PARAMETERS. IN THIS CASE, WE DESIRETO USESELF-STARTING CHARTING SCHEMES THAT MONITORTHE STATUES OFPROCESSES. IN THIS STUDY, WE CONSIDER LOGISTIC REGRESSION PROFILESWHICH HAVE BINARY RESPONSEVARIABLEAND PROPOSE A SELF-STARTING PROCEDURE TO MONITOR THE PROCESS. THE PERFORMANCE OF THE PROPOSED METHOD IS EVALUATED BY USING AVERAGE RUN LENGTH (ARL) CRITERION. THE RESULTS SHOWEDASATISFACTORY PERFORMANCE OFTHE PROPOSED CONTROL CHART.

DESPITE ALL ITS POTENTIALS, NEW INDUSTRIAL REVOLUTION ENABLED BY CYBER-PHYSICAL SYSTEMS (CPS), ON ITS WAY TO BE FULLY APPRECIATED STILL HAS MAJOR CONCERNS AND OBSTACLES WITH REGARDS TO DEPENDABILITY AND SECURITY. THIS STUDY TARGETS THESE CONCERNS BY PROPOSING A GENERIC MODEL FOR INTELLIGENT DISTRIBUTED DEPENDABILITY AND SECURITY SUPERVISION AND CONTROL MECHANISM, THAT ENABLES COMPONENTS TO AUTONOMOUSLY MEET THEIR OWN SECURITY AND DEPENDABILITY OBJECTIVES, THROUGH REAL-TIME DISTRIBUTED SUPERVISION AND CONTROL. IN ADDITION, A MULTI-AGENT SYSTEM (MAS) BASED IMPLEMENTATION APPROACH IS PROPOSED TO ENABLE FULL EXPLOITATION OF THE MODEL’S CAPABILITIES.

NOWADAYS BUSINESS INTELLIGENCE (BI) TOOLS PROVIDE THE DECISION SUPPORT ENVIRONMENT IN ENTERPRISE SYSTEMS LIKE ERP AND MAINLY REFERS TO COMPUTER-BASED TECHNIQUES USED IN IDENTIFYING, EXTRACTING AND ANALYZING BUSINESS DATA, SUCH AS SALES REVENUE BY PRODUCTS AND/OR DEPARTMENTS, OR BY ASSOCIATED COSTS AND INCOMES. THE PURPOSE OF THIS PAPER IS TO PROVIDE A UNIFIED FRAMEWORK FOR THE APPLICATION OF BUSINESS INTELLIGENCE (BI) IN ENTERPRISE SYSTEMS ENVIRONMENT WHICH RESULTS IN VALUE-ADDED QUALITY CONTROL AND MANAGEMENT SYSTEMS. THE RESEARCH FINDINGS SHOW THE BENEFITS OF ENTERPRISE SYSTEMS SUCH AS THE INTEGRATION OF ALL ASPECTS OF BUSINESS AND DATA ACCESS IN REAL TIME IN ALL PARTS OF THE ENTERPRISE SUCH AS QUALITY MANAGEMENT WITH BUSINESS INTELLIGENCE (BI) TOOLS REDUCE DISADVANTAGES OF THESE SYSTEMS AND ACCESS TO INFORMATION ON QUALITY MANAGEMENT TO BE COMBINED. THEREFORE, INTEGRATING THE BI AND QUALITY MANAGEMENT MODULE OF ENTERPRISE SYSTEMS CAN BE EXPANDED ENTERPRISE DATA COLLECTION AND ANALYSIS, AND ENABLE QUALITY MANAGERS TO PREDICT VARIOUS QUALITY, IT WILL FACILITATE DECISION-MAKING PROCESS. IN THIS PAPER CHALLENGES FACING ENTERPRISE SYSTEMS AND QUALITY MANAGEMENT SYSTEM ARE DISCUSSED. THEN THE BUSINESS INTELLIGENCE CAPABILITIES AND FEATURES ARE INTRODUCED WITH PROPOSING THE INTEGRATED FRAMEWORK FOR ENTERPRISE SYSTEMS AND BI IN THE QUALITY MANAGEMENT DESCRIBED, AND SUGGESTIONS FOR IMPROVEMENT ARE PRESENTED.

IN THIS PAPER WE PRESENT A CONSTRAINT PROGRAMMING MODEL IN ORDER TO FIND A FAIR SCHEDULE FOR A DOUBLE ROUND ROBIN TOURNAMENT (DRRT) WHICH IS A COMMON ISSUE IN THE FIELD OF SPORT SCHEDULING. IN A DRRT EACH PAIR OF TEAMS PLAY EACH OTHER TWO TIMES, ONCE IN EACH HALF-SEASON, DURING A SEASON COMPRISING TWO HALF-SEASONS. THE MOST CONVENTIONAL CONSTRAINT SETS IN DRRT PROBLEMS SUCH AS THE STRENGTH GROUPS, THE COMPLEMENTARY TEAMS, THE NUMBER OF BREAKS, AND GAME CONSTRAINTS HAVE BEEN CONSIDERED IN THIS RESEARCH TO MAKE A SCHEDULE AS FAIR AS POSSIBLE. THE MINIMIZATION OF THE TOTAL NUMBER OF THE BREAKS IS CONSIDERED AS THE OBJECTIVE FUNCTION IN THE MODEL. USING PRESENT MODEL, WE REACH A FEASIBLE SCHEDULE FOR IRAN’S SOCCER PRO-LEAGUE WITH 18 TEAMS.

ENVIRONMENTAL STRESS SCREENING PROGRAM, WHICH IS USED IN DEVELOPMENT PHASE OF MANUFACTURING, CAUSES DECREASE OR EVEN ELIMINATION OF HIDDEN FAULTS OF PRODUCTS BEFORE COMPETENCY TESTS. THIS CAN LEAD TO SIGNIFICANT IMPROVEMENT IN PRODUCT RELIABILITY AND DECREASE IN MAINTENANCE COSTS. DURING ENVIRONMENTAL STRESS SCREENING TEST, THE PRODUCT IS EXPOSED TO A CERTAIN ENVIRONMENTAL CONDITIONS SUCH AS TEMPERATURE, HUMIDITY AND VIBRATION IN A CERTAIN LEVEL FOR SOME AMOUNT OF TIMES. THE EXPOSURE TIME IS A VERY IMPORTANT PARAMETER THAT SHOULD BE DETERMINED ACCURATELY USING STATISTICAL METHODS. THE AIM OF THIS PAPER IS TO CALCULATE THE OPTIMAL EXPOSURE TIME FOR AN ENVIRONMENTAL STRESS SCREENING PROCESS USING WEIBULL DISTRIBUTION WHICH HAS WIDE APPLICATIONS IN RELIABILITY ANALYSIS. A CASE STUDY OF ELECTRONIC SETS IS THEN APPLIED TO ILLUSTRATE THE PROCESS STEP BY STEP. AFTER DETERMINATION OF WEIBULL PARAMETERS, OBTAINED RESULTS AND CHARTS ARE USED TO CALCULATE THE TIME PARAMETER OF SCREENING TEST FOR THE COMPONENTS.

SHELF SPACE PLANNING IS AN IMPORTANT PART OF RETAILING MANAGEMENT AND CONSISTS TOPICS SUCH AS ANALYSIS ON THE DEPENDENCE BETWEEN DEMAND AND INVENTORY AND ALSO DETERMINING THE ALLOCATION OF PRODUCTS TO THE SHELVES. DETERMINISTIC DEMAND IS ONE OF THE MOST COMMON ASSUMPTIONS IN THESE MODELS WHILE MOST OF THE TIME IN THE REAL WORLD WE ARE FACED WITH UNCERTAIN DEMAND. ON THE OTHER HAND DISPLAY FACING AREA IS AN ESSENTIAL VARIABLE IN THESE PROBLEMS BECAUSE OF DIFFERENT PHYSICAL FORMS OF GOODS AND ITS IMPACT ON SPACE REQUIREMENTS. HENCE WE DEVELOP THE SHELF SPACE OPTIMIZATION MODELS CONSIDERING OF STOCHASTIC DEMAND AND DISPLAY FACING AREA AND THEN USE A HYBRID APPROACH USING THE BASIC FORM OF THE BEES ALGORITHM AND A HEURISTIC ALGORITHM TO IMPROVE PERFORMANCE OF ALGORITHMS AS A SOLVING METHOD FOR THIS TYPE OF MODELS. IN THE END, THE SENSITIVITY ANALYSIS ON PARAMETERS AND ALSO PRICING POLICIES ANALYSIS IS MADE.

THIS STUDY ADDRESSES FLEXIBLE JOB SHOP SCHEDULING BY CONSIDERING STOCHASTIC MACHINE BREAKDOWN. IN THIS STUDY WE INTRODUCE PREDICTIVE SCHEDULING TO DEAL WITH MACHINE BREAKDOWN UNCERTAINTY AND THEN WE MAKE A COMPARISON WITH DETERMINISTIC SCHEDULING TO SHOW THE EFFECTIVENESS OF THE PROPOSED METHOD. SINCE FJS PROBLEMS ARE KNOWN AS NP-HARD AND ALSO ADDITIONAL COMPLEXITY DUE TO STOCHASTIC ENVIRONMENT ADDED UP, A META HEURISTIC SOLUTION ASSOCIATED WITH REALISTIC CONDITION OF STUDY HAS DEVELOPED. DEVELOPED SOLUTION METHOD CONSIDERS BREAKDOWN EVENTS AND SIMULATES OCCURRENCE OF BREAKDOWN IN THE REAL SCHEDULE. PROPOSED GENETIC ALGORITHM CONSISTS OF BOTH DETERMINISTIC AND PREDICTIVE SCHEDULING AND DEMONSTRATES EFFECTIVENESS OF PROPOSED PREDICTIVE SCHEDULING.

BUILDINGS HAVE A SIGNIFICANT IMPACT ON ENERGY USAGE AND THE ENVIRONMENT. MUCH OF THE RESEARCH IN ARCHITECTURAL SUSTAINABILITY HAS CENTERED ON ECONOMICALLY ADVANCED COUNTRIES BECAUSE THEY CONSUME THE MOST ENERGY AND HAVE THE MOST RESOURCES. HOWEVER, SUSTAINABLE ARCHITECTURE IS IMPORTANT IN DEVELOPING COUNTRIES, WHERE THE ENERGY CONSUMPTION OF THE BUILDING SECTOR IS INCREASING SIGNIFICANTLY. THE AIMS OF THIS STUDY ARE INVESTIGATING USING THE HYBRID SYSTEM, WHICH FORMED BY INTERCONNECTING TWO SOURCE OF RENEWABLE ENERGY AS SOLAR AND WIND ALONG WITH CITY GRID FOR COMPENSATION PURPOSES WHEREVER IT IS REQUIRED. IN THIS STUDY, AFTER LITERATURE REVIEW, WE CONSIDER THE CASE STUDY AND ITS ASSUMPTIONS, SYSTEM DESCRIPTION AND ITS CHARACTERISTICS FOLLOWING BY DISCUSSION OF RENEWABLE ENERGY SOURCES IN MORE DETAILS. FURTHERMORE, THE OPTIMIZATION AND PREDICTION ISSUES AND THE DATA UNCERTAINTY IN THIS FIELD HAVE CONSIDERED. THEN, THE NET LOGO PROGRAMMING LANGUAGE IS UTILIZED FOR SIMULATION OF THE SYSTEM.

IN THIS PAPER, ONE OF THE MOST IMPORTANT CRITERION IN PUBLIC SERVICES QUALITY NAMED AVAILABILITY IS EVALUATED BY USING ARTIFICIAL NEURAL NETWORK (ANN). IN ADDITION, THE AVAILABILITY VALUES ARE PREDICTED FOR FUTURE PERIODS BY USING EXPONENTIAL WEIGHTED MOVING AVERAGE (EWMA) SCHEME. RESULTS BASED ON COMPARATIVE STUDIES BETWEEN FOUR METHODS BASED ON ANN AND BY CONSIDERING THE SEVERAL CONDITIONS FOR THE EFFECTIVE PARAMETERS IN ANN SHOW THAT, THE GENERALIZED REGRESSION METHOD IS THE BEST METHOD FOR PREDICTING THE AVAILABILITY. FURTHERMORE, THE RESULTS OF THE EWMA METHOD IS ALSO SHOWS THE SUITABLE PERFORMANCE FOR PREDICTING THE AVAILABILITY VALUES IN FUTURE PERIODS.

INTRODUCTION IN MOST INVENTORY MODELS, ASSUMED THAT THE ITEMS CAN BE UNLIMITED IN TIME, STORED FOR FUTURE DEMAND AND THEIR QUANTITY AND QUALITY DOES NOT CHANGE OVER TIME, HOWEVER, CERTAIN TYPES OF PRODUCT THAT, OVER TIME HAS DETERIORATED OR ARE UNUSABLE, SUCH AS FOODS, HUMAN BLOOD, ALCOHOL, DRUGS AND SO ON. AS A RESULT IF THE DECAY RATE IS SIGNIFICANTLY AMOUNT, ITS EFFECT CANNOT BE NEGLECTED. IN MATHEMATICAL MODELING, INVENTORY CONTROL PROBLEM, THAT BEGAN WITH CLASSIC PROBLEM ECONOMIC ORDER QUANTITY OF HARRIS [1], IT IS ASSUMED THAT THE PRODUCTS HAVE INFINITE LIFE...

SOCIAL MEDIA WEBSITES CAPTURED WEB SPACE. THE MEMBERS OF THESE MEDIA'S INCREASING DAILY. WITH THE DATA SHARED BY PEOPLE, RESEARCHERS TRY TO USE THEM IN A PROPER WAY TO HELP RECOMMENDER SYSTEMS. ONE OF THE HOT RESEARCH AREAS IS USER INTEREST DETECTION. INTELLIGENT WEB SYSTEMS TRY TO EXTRACT USER PRIMITIVE INTEREST FROM CONTENTS WHICH ARE SHARED BY USERS. WHILE MOST OF THE WORKS CONCENTRATE ON EXTRACTING USER INITIAL INTEREST, LESS ATTEMPT DEDICATED TO UNDERSTANDING LATENT ONES. IN THIS PAPER, WE DEMONSTRATE HOW WORD EMBEDDING METHODS COULD HELP US TO ENRICH USER INTERESTS PROFILE. WE GENERATING STATE-OF-ART USER INTEREST MODELING WHICH DEPLOYS WORD2VEC METHOD FOR ENRICHING USER INITIAL INTERESTS THAT EXTRACTED FROM USER'S TWITTER ACCOUNT. OUR EXPERIMENTAL RESULTS DEMONSTRATE THAT USING SEMANTIC SIMILARITY MEASURES, ESPECIALLY WHEN USING WORD EMBEDDING METHODS, OUTPERFORM TRADITIONAL METHODS. EMPIRICAL RESULTS SHOW THAT ENRICHING USER INTEREST PROFILE LEADS TO BETTER PERSONALIZED CONTENT BASED RECOMMENDATION.

GAS SUPPLY CHAIN IS A COMPLEX AND HUGE NETWORK WHICH IS IN NEED OF HEAVY INVESTMENTS IN ALL OF THE STAGES. LIQUEFYING THE NATURAL GAS IS THE COMMON WAY TO FACILITATE THE TRANSPORTATION OF NATURAL GAS. THE EMERGENCE OF SUPPLIERS WITH LARGE GAS RESERVES AND DISAPPEARANCE OF CONVENTIONAL CLAUSES STIMULATE THE GLOBAL LNG TRADE. THIS PAPER AIMS TO PROVIDE AN OPTIMIZATION MODEL FOR THE NATURAL GAS SUPPLY CHAIN NETWORK DESIGN WHILE CONSIDERING THE SELECTION OF CONTRACTS FROM THE PERSPECTIVE OF AN LNG BUYER COMPANY. THE ELABORATED MODEL IS ABLE TO CONSIDER THE BEST COMBINATION OF FACILITIES LOCATION AND PIPELINES SUPPLIERS AND CONTRACTS IN GAS SUPPLY CHAIN NETWORK DESIGN THAT ADDRESSES VARIOUS ASPECTS, SUCH AS CONTRACT TIMINGS AND LENGTHS, DEMANDS, PRICE FORMULATIONS, PURCHASE COMMITMENTS, DELIVERY TERMS AND GAS TECHNICAL SPECIFICATIONS. THE DEVELOPED MODEL IS SOLVED USING GAMS 24.4.6 OPTIMIZATION SOFTWARE AND RESULTS SHOW THE APPLICABILITY AND EFFICIENCY OF THE PROPOSED MATHEMATICAL MODEL.

OPTIMUM DESIGN AND CONTROL OF A COMBINED COOLING, HEATING AND POWER GENERATION (CCHP) SYSTEM, IN ADDITION TO THE ECONOMIC BENEFITS, COULD BE PROFITABLE IN ENVIRONMENTAL AND ENERGY CONSUMPTION ASPECTS. THE AIM OF THIS STUDY IS TO DETERMINE THE SYSTEM’S PERFORMANCE UNDER FIVE DIFFERENT STRATEGIES. IN A REAL CASE STUDY, A CCHP SYSTEM IS DESIGNED FOR AN EDUCATIONAL COMPLEX LOCATED IN MAHMOUDABAD, MAZANDARAN, IRAN. THE OBJECTIVE IS TO MINIMIZE CAPITAL AND OPERATIONAL COSTS, ENERGY CONSUMPTION, AND CO2 EMISSIONS OF THE SYSTEM. DUE TO THE COMPLEXITIES OF THE MODEL, GENETIC ALGORITHM (GA) AND PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM ARE USED TO FIND THE OPTIMAL VALUES OF THE DECISION VARIABLES. THE RESULTS SHOW THAT USING FEL STRATEGY CO2 EMISSIONS REDUCES IN COMPRESSION TO FTL STRATEGY. FURTHERMORE, USING MULTIPLE POWER GENERATION UNITS UNDER FTL STRATEGY EVENTUATES THE LEAST COST BUT INCREASES CO2 EMISSIONS AND ENERGY CONSUMPTION IN COMPRESSION TO FEL STRATEGY.

NOWADAYS, SUPPLIERS PLAY AN IMPORTANT ROLE IN DEVELOPMENT OF SUSTAINABLE SUPPLY CHAIN MANAGEMENT (SCM). IN THIS STUDY, A NOVEL MULTI-OBJECTIVE MODEL HAS BEEN PROPOSED WHICH TAKES INTO ACCOUNT THE IMPORTANCE OF OBJECTIVES IN AN EFFICIENT WAY AND CONSIDERS THE UNCERTAINTY OF REAL WORLD PROBLEMS. IN ORDER TO CONSIDER THE MENTIONED UNCERTAINTY, THE INPUT DATA ARE DEFINED AS GREY NUMBERS. TO SOLVE THE PROPOSED MATHEMATICAL MULTI-OBJECTIVE MODEL BASED ON GREY NUMBERS, IT HAS BEEN FORMULATED IN THE FORM OF FUZZY GOAL PROGRAMMING (FGP); THEN, IT HAS BEEN CONVERTED TO GREY LINEAR PROGRAMMING (GLP). EVENTUALLY, A SENSITIVITY ANALYSIS HAS BEEN CARRIED OUT IN ORDER TO SHOW THE PERFORMANCE OF THE PROPOSED MODEL.

ONE OF THE MOST WIDELY USED MULTIVARIATE CONTROL CHARTS IS THE HOTELLING T2. IN ORDER TO DESIGN A HOTELLING T2CONTROL CHART, THE MEAN VECTOR (M) AND THE VARIANCE-COVARIANCEMATRIX (S) MUST BE FIRST ESTIMATED. THE CLASSICAL ESTIMATORS ARE USUALLY USED TO ESTIMATE THESE TWO PARAMETERS. THEY ARE DEFINED BASED ON ASSUMPTIONS WHICH ARE NOT ALWAYS VALID. ONE WEAKNESS OF THE CLASSICAL ESTIMATORS IS THEIR SENSITIVITY TO THE PRESENCE OF OUTLIERS. ONE WAY TO DEAL WITH OUTLIERS IS TO USE ROBUST ESTIMATORS. IN THIS STUDY, A ROBUST HOTELLING T2CONTROL CHART IS PROPOSED. THE MEAN VECTOR FOR THE CONTROL CHART IS OBTAINED USING THE SAMPLE MEDIAN. THE MEDIAN ABSOLUTE DEVIATION FROM THE SAMPLE MEDIAN AND THE COMEDIAN ESTIMATORS ARE USED TO CALCULATE THE ELEMENTS OF THE VARIANCE-COVARIANCE MATRIX. THE PROPOSED ROBUST ESTIMATORS OF THE MEAN VECTOR AND THE VARIANCE-COVARIANCE MATRIX ARE COMPARED WITH THE SAMPLE MEAN VECTOR AND THE SAMPLE VARIANCE-COVARIANCE MATRIXTHROUGH EFFICIENCY AND ROBUSTNESS MEASURES. THE PERFORMANCES OF THE PROPOSED ROBUST HOTELLING T2CONTROL CHART AND THE CLASSICAL ONE ARE ALSO COMPARED BY MEANS OF ARL. THE SIMULATION RESULTS REVEAL THAT, THE PROPOSED ROBUST HOTELLING T2CONTROL CHART HAS A MUCH BETTER PERFORMANCE THAN THE CLASSICAL HOTELLING T2.

SUPPLIER SELECTION IS ONE OF THE INFLUENTIAL DECISIONS FOR EFFECTIVENESS OF PURCHASING AND MANUFACTURING POLICIES UNDER COMPETITIVE CONDITIONS OF THE MARKET. THIS PAPER DEVELOPS A NADIR COMPROMISE PROGRAMMING MODEL FOR DECISION-MAKING UNDER UNCERTAINTY ON THE SUPPLIER SELECTION WITHIN THE FRAMEWORK OF BINARY PROGRAMMING. DEPENDING ON CONDITION OF UNCERTAINTY, THREE STATUSES ARE TAKEN INTO CONSIDERATION AND A SOLUTION APPROACH IS PROPOSED FOR EACH STATUS. A PURE DETERMINISTIC NCP MODEL IS PRESENTED FOR SOLVING THE PROBLEM IN WHITE CONDITION (DATA CERTAINTY) AND A SOLUTION APPROACH RESULTED FROM COMBINATION OF NCP AND STOCHASTIC PROGRAMMING IS INTRODUCED TO SOLVE THE MODEL IN BLACK (DATA UNCERTAINTY) SITUATION. THE PAPER ALSO PROPOSES A NCP MODEL UNDER CERTAINTY AND UNCERTAINTY FOR SOLVING PROBLEM UNDER GREY (COMBINATION OF DATA CERTAINTY AND UNCERTAINTY) CONDITIONS. THE PROPOSED APPROACHES ARE ILLUSTRATED FOR A REAL PROBLEM WITH MULTIPLE CRITERIA AND A SIMULATION APPROACH IS DESIGNED TO EXAMINE CAPABILITIES OF THE PROPOSED MODEL.

IN THIS MODEL, ECONOMIC OBJECTIVE (OPENING COST OF DEPOTS AND TREATMENT FACILITY AND TRANSPORTATION COST REGARD TO LOADING TIME AND WAITING TIME) AND SOCIETAL OBJECTIVE FUNCTION; THAT IS, NEGATIVE EFFECT, OF TREATMENT FACILITIES WHICH ARE CLOSE TO TOWNS, FOR WASTE COLLECTION PROBLEM IS CONSIDERED UNDER UNCERTAINTY NOTICING CONGESTION IN THE TREATMENT FACILITIES. EACH TREATMENT FACILITIES ARE MODELED AS AN M/M/C QUEUING SYSTEM. THEN LOCATE DEPOTS AND TREATMENT FACILITIES AND DESIGN THE ROUTES STARTING FROM DEPOTS TO SERVE CUSTOMERS. ALSO MODIFIED WEIGHTED-SUM APPROACH AND MAXIMIZE MINIMUM APPROACH IS USED TO VALIDATE THE PROPOSED MODEL WITH GAMS.

IN NEWSVENDOR PROBLEM (NVP), A DECISION MAKER SHOULD ORDER BEFORE SELLING SEASON WHEN THE BALANCE OF ORDERING IS REQUIRED UNDER DEMAND UNCERTAINTY. THE DIFFERENT EXTENSIONS OF NVP IN ACADEMY AND PRACTICE ASSUME THAT THE DECISION MAKERS ORDER AT A FAMILIAR OPTIMAL ORDERING LEVEL SO CALLED CRITICAL RATIO. HERE, WE DESIGN AN EXPERIMENT BASED ON BEHAVIORAL ASPECTS AND SHOW THAT IN REALITY, PEOPLE DEVIATE FROM OPTIMAL ORDERING LEVELS. OUR FINDINGS SHOW THAT THE DEVIATIONS CAN BE INTERPRETED UNDER RISK-AVERSION IN PARTICULAR STOCK-OUT AVERSION OF THE SUBJECTS. MOREOVER, WE OBSERVE THAT THESE DEVIATIONS ARE NOT DEPENDENT TO DIFFERENT OPTIMAL LEVELS WHICH REQUIRE MORE EXPERIMENT DESIGN IN ORDER TO DESCRIBE THIS BEHAVIORAL PHENOMENON.

NOWADAYS, NATURE-INSPIRED PLAYS A KEY ROLE ESPECIALLY IN TRANSPORTATION PROBLEMS AND OPERATION MANAGEMENT PROBLEMS. THIS STUDY PRESENTS THE APPLICATION OF A NOVEL NATURE-INSPIRED ALGORITHM TO THE BASIC VEHICLE ROUTING PROBLEM (VRP) IN THE LARGE SCALE NETWORK, IN WHICH CUSTOMERS OF KNOWN DEMAND ARE SUPPLIED FROM A SINGLE DEPOT. VEHICLES ARE SUBJECT TO A WEIGHT LIMIT AND, IN SOME CASES, TO A LIMIT ON THE DISTANCE TRAVELLED. ONLY ONE VEHICLE IS ALLOWED TO SUPPLY EACH CUSTOMER. FURTHERMORE, TO ADDRESS THE PROPOSED PROBLEM, RDA INSPIRED BY RED DEER’S MATING AND PRESENTED RECENTLY AS ONE OF NOVEL METAHEURISITC METHODS IS INTRODUCED. THIS ISSUE AIMS TO EXPLORE THE RDA ON THE PROPOSED VRP FOR THE FIRST TIME. IN ADDITION, COMPUTATIONAL RESULTS ARE COMPUTED FOR THE RDA WHICH IS PUT FORWARD. FURTHER RESULTS ARE GIVEN USING AN IMPERIALIST COMPETITIVE ALGORITHM AND GENETIC ALGORITHM, SHOWING THAT THIS APPROACH IS COMPETITIVE WITH OTHER STRONG METAHURISTICS IN TERMS OF SOLUTION TIME AND QUALITY.

FACILITY LAYOUT PROBLEM HAS A CONSIDERABLE EFFECT ON MANUFACTURING COST; HENCE, IT CAN BE VIEWED AS A CRUCIAL SUBJECT IN THE DESIGN OF MANUFACTURING SYSTEMS OPERATING AT DYNAMIC AND STOCHASTIC SITUATIONS IN PARTICULAR. THIS PAPER PROPOSES A NEW QUADRATIC ASSIGNMENT-BASED MATHEMATICAL MODEL FOR CONCURRENT DESIGN OF ROBUST INTER AND INTRA-CELL LAYOUTS IN A MULTI-PERIOD AND UNCERTAIN ENVIRONMENT OF MANUFACTURING SYSTEMS. THE PRODUCT DEMANDS ARE PRESUMED TO BE INDEPENDENT NORMALLY DISTRIBUTED RANDOM VARIABLES WITH KNOWN EXPECTATION THAT CHANGE FROM PERIOD TO PERIOD AT RANDOM. IN THE PROPOSED MODEL, TIME VALUE OF MONEY IS ALSO CONSIDERED. TO VALIDATE THE PROPOSED MODEL, A RANDOMLY GENERATED TEST PROBLEM IS SOLVED BY USING SIMULATED ANNEALING (SA) ALGORITHM PROGRAMMED IN MATLAB. FINALLY, THE RESULTS ARE ANALYZED FROM STATISTICAL AND SENSITIVITY POINTS OF VEIW.

THIS PAPER PRESENTS A BI-OBJECTIVE MODEL FOR A GREEN TRUCK SCHEDULING AND ROUTING PROBLEM AT A CROSS-DOCKING SYSTEM. THIS MODEL DETERMINES THREE KEY DECISIONS AT THE CROSS DOCK AS FOLLOWS: 1) DEFINING A SEQUENCE AND SCHEDULE OF INBOUND TRUCKS AT THE RECEIVING DOOR, 2) SPECIFYING A SEQUENCE AND SCHEDULE OF OUTBOUND TRUCKS AT THE SHIPPING DOOR, AND 3) DETERMINING THE ROUTES OF THE OUTBOUND TRUCK WHILE SERVING CUSTOMERS. THE FIRST OBJECTIVE FUNCTION IS RELATED TO RESPONSIVENESS OF THE NETWORK THAT MINIMIZES TIME WINDOW VIOLATIONS AND THE SECOND OBJECTIVE FUNCTION MINIMIZES TOTAL FUEL CONSUMPTION OF TRUCKS IN ORDER TO CONSIDER THE ENVIRONMENTAL FACTOR OF THE NETWORK. ALSO, A LEARNING EFFECT IS CONSIDERED IN LOADING AND UNLOADING PROCESS TIMES. TO SOLVE THE BI-OBJECTIVE MODEL, AN ARCHIVED MULTI-OBJECTIVE SIMULATED ANNEALING (AMOSA) IS USED AND MODIFIED. FINALLY, 10 TEST PROBLEMS ARE SOLVED AND THE EFFICIENCY OF THE PROPOSED AMOSA IS COMPARED WITH AN E-CONSTRAINT METHOD.

SMART PROPERTIES OF MANUFACTURING UNITS INEVITABLY INTRODUCE NOVEL NETWORK DRIVEN CONCURRENCY PRINCIPLES TO MANUFACTURING NETWORKS. PLAYING THIS GAME WILL UNRAVEL THE FULL LIST OF ADVANTAGES OF THE NETWORK COMPARED TO THE SYSTEMS, ESPECIALLY UNDER TIME PRESSURE OR FACING FREQUENT AND MAJOR MODIFICATIONS. THE ACTUAL VALUE CHAIN, AN OBJECT PASSES, IS ONLY KNOWN EX-POST. SPECIFICALLY, DESIGNED CHECKS AND VERIFICATIONS, NEGOTIATIONS AND DEPENDABILITY MECHANISMS WILL OPTIMIZE OPERATION UNITS’ BEHAVIOR AND ALL COMMUNICATION LINKS.

SELECTING AN ORGANIZATIONAL SYSTEM IS A COMPLEX AND TIME CONSUMING PROCESS. CONSIDERING A SYSTEMATIC AND COMPREHENSIVE POLICY FOR SELECTING AN ERP IS CRUCIAL TO THE PROJECT’S SUCCESS.. AMONG THE STAKES THAT THE ORGANIZATION MUST OVERCOME PRIOR TO COMMENCEMENT AND IMPLEMENTATION OF THE PROJECT IS IMPROPER SELECTION OF THE SYSTEM. THE USE OF ERP IN SMALL AND MEDIUM-SIZED ORGANIZATIONS IS A DELICATE MATTER. FUZZY MULTI-CRITERIA DECISION-MAKING PROCEDURE CAN BE EMPLOYED TO SELECT THE APPROPRIATE OPTIONS ACCORDING TO VARIOUS CRITERIA AND THE WEIGHT OF DIFFERENT CONDITIONS IN THE PRESENCE OF UNCERTAINTY. THIS STUDY AIMS TO SELECT PROPER ERP SYSTEM FOR FOOD ERP SME’S COMPANY ACTIVE IN PRODUCTION AND EXPORTING MUSHROOMS TO PERSIAN GULF DISTRICT COUNTRIES (NAMELY IRAQ AND UNITED ARAB EMIRATES), USING FUZZY MULTI-CRITERIA DECISION-MAKING METHOD AND SHANNON ENTROPY TECHNIQUE.

CHRONIC DISEASES ARE THE MAIN CAUSE OF GLOBAL MORTALITY IN RECENT DECADES AND DUE TO THE LACK OF ABSOLUTE TREATMENT AND NEED TO PERMANENT CONTROL, IMPOSES HIGH COSTS TO THE HEALTH SYSTEM OF THE COUNTRY. ONE OF THE MOST IMPORTANT CHRONIC DISEASES IS CARDIOVASCULAR DISEASES WHICH ARE THE FIRST CAUSE OF DEATH IN IRAN, ACCORDING TO THE WORLD HEALTH ORGANIZATION’S REPORT. ANALYZING THE PROCESS OF CATCHING THESE DISEASES AND ITS FEEDBACK CONSEQUENCE ON THE HEALTH ECONOMY, ARE THE MAIN PROBLEM OF THIS STUDY. THEREFORE, IN THIS RESEARCH, IN ADDITION TO THE REPRESENTATION OF CARDIOVASCULAR CHRONIC DISEASES GENERATOR AND GROWTH SYSTEM STRUCTURE, BASED LIMIT TO GROWTH ARCHETYPE IN SYSTEM THINKING THEORY, BALANCING AND ADJUSTING SOLUTION AND STRATEGIES FOR INSURANCE COST EFFECTIVE MANAGEMENT WILL PRESENT. THE RESULTS SHOW THAT OBESITY, LACK OF PHYSICAL ACTIVITY AND UNSUITABLE NUTRITION STYLE ARE THE MOST IMPORTANT REINFORCING LOOP IN THE SYSTEM AND THEY IMPOSE HIGH COSTS TO THE HEALTH ECONOMY SYSTEM. ALSO, BY REPLACING PART OF THE INSURANCE COVERING COST WITH DEVELOPMENT COSTS OF PREVENTIVE FACTORS SUCH AS PHYSICAL ACTIVITY INFRASTRUCTURES DEVELOPMENT, INSURANCE COSTS EFFECTIVE MANAGEMENT CAN BE ACHIEVED.

THE AIM OF THIS STUDY WAS TO EVALUATE THE EFFECT OF CUSTOMER KNOWLEDGE AND CUSTOMER RELATIONSHIP MANAGEMENT IN THE QUALITY OF SERVICES IN THE SARMAD INSURANCE. THE METHOD USED IN THIS RESEARCH IS CORRELATION. THEREFORE, IN THIS STUDY, ALL MEMBERS OF THE COMMUNITY POPULATION ARE AN INSURANCE COMPANY SARMAD, 214 PEOPLE WERE RANDOMLY CHOSEN. DATA COLLECTION TOOLS INCLUDE QUESTIONNAIRE, CUSTOMER KNOWLEDGE, QUALITY OF SERVICE AND CUSTOMER RELATIONSHIP MANAGEMENT. AFTER SCORING QUESTIONNAIRE AND DATA EXTRACTION WITH SPSS AND THE EFFECT OF CUSTOMER KNOWLEDGE AND CUSTOMER RELATIONSHIP MANAGEMENT IN SERVICE QUALITY OFSARMAD INSURANCE COMPANY HAD BEEN SHOWNWITH STATISTICAL TEST.

IN THIS PAPER THE REDUNDANCY AND IMPERFECT OPPORTUNISTIC MAINTENANCE OPTIMIZATION OF A MULTI-STATE WEIGHTED K-OUT-OF-N SYSTEM IS FORMULATED. THE OBJECTIVE IS TO DETERMINE THE K-OUT-OF-N SYSTEM REDUNDANCY LEVEL AND THE MAINTENANCE STRATEGY MINIMIZING THE LIFE CYCLE COST SUBJECT TO AN AVAILABILITY CONSTRAINT. A NEW CONDITION BASED OPPORTUNISTIC MAINTENANCE APPROACH IS DEVELOPED. DIFFERENT COMPONENT HEALTH STATE THRESHOLDS ARE INTRODUCED FOR IMPERFECT MAINTENANCE OF FAILED SUBSYSTEMS AND WORKING SUBSYSTEMS AND PREVENTIVE DISPATCHING OF MAINTENANCE TEAMS. IN ADDITION, A SIMULATION METHOD IS DEVELOPED TO EVALUATE THE PERFORMANCE MEASURES OF THE SYSTEM CONSIDERING DIFFERENT TYPES OF SUBSYSTEMS, MAINTENANCE ACTIVATION DELAYS AND DURATIONS, LIMITED NUMBER OF MAINTENANCE TEAMS, AND DISCRETE INSPECTION OF THE SYSTEM. ALSO, A MULTI-SEED TABU SEARCH HEURISTIC ALGORITHM IS ALSO PROPOSED TO SOLVE THE FORMULATED PROBLEM. AN APPLICATION TO THE OPTIMAL DESIGN OF A WIND FARM IS PROVIDED TO ILLUSTRATE THE PROPOSED APPROACH.

SUPPLYING OF BLOOD AND BLOOD PRODUCTS IS ONE OF THE MOST CHALLENGING ISSUES IN THE HEALTHCARE SYSTEM SINCE BLOOD IS AS EXTREMELY PERISHABLE AND VITAL GOOD AND DONATION OF BLOOD IS A VOLUNTARY WORK. IN THIS PAPER, WE PROPOSE A TWO-STAGE STOCHASTIC SELECTIVE-COVERING-INVENTORY-ROUTING (SCIR) MODEL TO SUPPLY WHOLE BLOOD UNDER UNCERTAINTY. HERE, SET OF DISCRETE SCENARIOS ARE USED TO DISPLAY UNCERTAINTY IN STOCHASTIC PARAMETERS. BOTH OF THE FIXED BLOOD CENTER AND BLOODMOBILE FACILITIES ARE CONSIDERED IN THIS STUDY. WE SUPPOSE THAT THE NUMBER OF BLOODMOBILES IS INDICATED IN THE FIRST STAGE BEFORE KNOWING WHICH SCENARIO IS OCCURRED. TO VERIFY THE VALIDATION OF THE PRESENTED SCIR MODEL TO SUPPLY WHOLE BLOOD, WE EXAMINE THE IMPACT OF PARAMETERS VARIATION ON THE MODEL OUTPUTS AND COST FUNCTION USING THE CPLEX SOLVER. ALSO THE RESULTS OF COMPARISON BETWEEN THE STOCHASTIC APPROACH AND EXPECTED VALUE APPROACH ARE DISCUSSED.

SURGICAL THEATER CONSISTS OF OPERATING AND RECOVERY ROOMS AND INCLUDES A MAJOR PART OF THE COSTS AND REVENUES OF A HOSPITAL. MOREOVER, THE DIFFERENT WARDS OF THE SURGICAL THEATER ARE IN A WIDE RELATIONSHIP WITH THE OTHER WARDS OF THE HOSPITAL AND INFLUENCE THEM. THUS, IMPROVING THE PERFORMANCE OF THE SURGICAL THEATER NOT ONLY INCREASES ITS PROFITABILITY, BUT ALSO IT INCREASES THE QUALITY OF THE PROVIDED SERVICES IN THE OTHER WARDS. HENCE, THE SCHEDULING OF THE SURGICAL THEATER IS A CRUCIAL AND CHALLENGING AFFAIR. IN THIS STUDY, WE PRESENT A NEW AND COMPREHENSIVE MODEL FOR THE DAILY SCHEDULING OF THE ELECTIVE PATIENTS BY CONSIDERING ALL RESOURCES AS WELL AS THE CAPACITY OF THE POSTOPERATIVE CARE UNITS. MOREOVER, WE AIM TO MINIMIZE THE UNDERUTILIZATION AND OVERUTILIZATION COST OF THE OPERATING ROOMS BY CONSIDERING THE OTHER CONSTRAINTS IN THE SURGICAL THEATER SUCH AS AVAILABILITY OF THE OPERATING ROOMS, SURGEONS, EQUIPMENT, HUMAN RESOURCES, AND NON-RENEWABLE RESOURCES. FINALLY, A REAL-LIFE EXAMPLE IS PROVIDED TO SHOW THE APPLICABILITY OF THE PROPOSED MODEL AND EVALUATE ITS PERFORMANCE IN COMPARISON WITH THE ACTUAL SCHEDULE SUGGESTED BY THE OPERATING ROOM MANAGER. THE RESULTS SHOWED THAT THE PROPOSED MODEL HAS A BETTER PERFORMANCE IN COMPARISON WITH THE ACTUAL SCHEDULE USED IN THE HOSPITAL.

UNDER CONDITIONS OF EXPANDING ENVIRONMENTAL IMPORTANCE FROM BUSINESS SECTORS, ORGANIZATIONS IN SUPPLY CHAINS HAVE PERCEIVED THE SIGNIFICANCE OF GREENING THEIR SUPPLY CHAIN WITHIN GREEN SUPPLIER DEVELOPMENT PROGRAMS. DIFFERENT ARTICLES HAVE BEGUN TO INVESTIGATE THE BETWEEN CONNECTIONS BETWEEN GREEN SUPPLY CHAIN MANAGEMENT AND SUPPLIER PERFORMANCE. MUCH OF THIS PERFORMANCE CAN BE ACCOMPLISHED ONLY WITH SUPPLIERS INCLUSION IN GREEN SUPPLIER DEVELOPMENT PROGRAMS. HOWEVER, THE STUDIES CONCENTRATING ON GREEN SUPPLIER DEVELOPMENT PROGRAMS IS VERY LIMITED. TO ADDRESS THIS GAP IN THE LITERATURE, WE PRESENT A NEW DECISION MODEL BASED ON INTERVAL VALUED 2-TUPLE LINGUISTIC PREFERENCES AND COMPROMISE SOLUTION FOR EVALUATING GREEN SUPPLIER'S PERFORMANCE. DUE TO THE SUPPLY CHAIN-EXPERTS’ DIFFERENT BACKGROUNDS AND PREFERENCES, SOME OF WHICH MAY BE IMPRECISE AND UNCERTAIN. THEN, A CASE STUDY FROM THE RECENT LITERATURE IN THE MANUFACTURING INDUSTRY IS PRESENTED AND SOLVED BY THE PROPOSED DECISION MODEL UNDER UNCERTAIN CONDITIONS.

THIS PAPER ATTEMPTS TO BUILD EFFICIENT SUPPLIER EVALUATION AND SELECTION SYSTEMS IN ORDER TO SUPPLYING REQUIRED PRODUCTS WITH HIGH QUALITY, AT THE RIGHT MOMENT WITH MINIMUM DELIVERY TIME AND AT A REASONABLE COST; TO COMPENSATE LOSSES ARISING FROM THE RISK OF SANCTIONS IN IRAN’S OIL & GAS DRILLING INDUSTRY. IN THE PROPOSED STUDY, TWO GENERAL CLASSES OF REQUIRED ITEMS AND TWO DIFFERENT CLASSES OF SUPPLIERS ARE CONSIDERED. IN ORDER TO EVALUATION AND SELECTION OF THE ADMISSIBLE SUPPLIERS, AHP TECHNIQUE IS USED. ALSO, A MULTI-OBJECTIVE LINEAR PROGRAMMING MODEL BASED ON TOTAL COST MINIMIZATION, TOTAL RISK MINIMIZATION, AND MAXIMIZING THE TOTAL VALUE OF PURCHASING, IS PROPOSED TO THE BEST SELECTION OF SUPPLIERS AND ALLOCATION OF ORDERS. A NUMERICAL EXAMPLE IS PRESENTED TO DEMONSTRATE THE APPLICABILITY OF THE PROPOSED MODEL.

FIXED-CHARGE TRANSPORTATION PROBLEM (FCTP) IS A PRIMARY PROBLEM IN SUPPLY CHAIN MANAGEMENT. TO SOLVE SUCH AN NP-HARD PROBLEM TWO METAHEURISTICS HAVE BEEN PROPOSED. SINCE WE COULD NOT FORMULATE REAL WORLD AS AN EXACT PROBLEM, THEREFORE IT IS NECESSARY TO DESCRIBE AN APPROXIMATE AND A FUZZY MODEL. IN THIS PAPER BOTH FIXED COSTS AND VARIABLE COSTS ARE CONSIDERED AS THE FUZZY NUMBERS. AS A NOVELTY APPROACH, WE CREATED A PROCEDURE FOR CONVERTING THE CONTINUOUS NUMBERS TO THE DISCRETE NUMBERS. IN THIS PAPER TWO ALGORITHMS INCLUDED SA AND WHALE OPTIMIZATION ALGORITHM (WOA) ARE DEVELOPED. BESIDES. THIS PAPER PROPOSES NEW APPROACHES IN SOLUTION ALGORITHMS USING BOTH SPANNING TREE BASED PRÜFER NUMBER AND PRIORITY BASED REPRESENTATION. ALSO, TAGUCHI METHOD IS USED TO GUARANTEE THE PROPER PERFORMANCE OF ALGORITHMS. IN ADDITION, SEVERAL VARIOUS PROBLEMS WITH DIFFERENT SIZES ARE GENERATED TO ASSESSMENT THE CAPABILITY OF THE ALGORITHMS AND COMMERCIAL SOFTWARE ACCORDING TO THE REAL WORLD CASE.

IN THIS STUDY, WE HAVE PRESENTED A MIXED INTEGER PROGRAMMING MODEL FOR THE RELIABLE LOCATION-ALLOCATION PROBLEM. THE MODEL DETERMINES THE LOCATED DISTRIBUTION CENTERS AND ALLOCATED CUSTOMERS TO MINIMIZE TOTAL NETWORK COST. FURTHERMORE, WE USED TO IMPROVE THE RELIABILITY OF THE NETWORK USING CORRELATED GEOGRAPHICAL FAILURE PROBABILITY. THE CORRELATED FAILURE PROBABILITY OF THE ARCS BETWEEN THE DISTRIBUTION CENTERS IS ESTIMATED USING A SPATIAL STATISTIC MODEL. FINALLY, WE SOLVE THE MODEL USING CPLEX SOLVER VERSION 12.5. A DISTRIBUTION COMPANY IN THE NORTH-KHORASAN PROVINCE IS USED AS AN EXAMPLE FOR THIS MODEL. THE NUMERICAL RESULTS HAVE SHOWN IMPROVING THE FAILURE PROBABILITY CAN REDUCE THE TOTAL COST OF THE SUPPLY CHAIN NETWORK.

IN THIS PAPER, WE STUDY A SUPPLY CHAIN NETWORK DESIGN PROBLEM WITH ENVIRONMENTAL CONCERNS. THERE ARE CUSTOMERS WITH PARTICULAR DEMANDS AND POTENTIAL PLACES WHICH ARE CANDIDATE TO BE DISTRIBUTION CENTERS. EACH OF THE POTENTIAL DCS CAN SHIP TO ANY OF THE CUSTOMERS. THREE TYPES OF COSTS ARE CONSIDERED; ENVIRONMENTAL INVESTMENT COST AND OPENING COST, ASSUMED FOR OPENING A POTENTIAL DC PLUS SHIPPING COST PER UNIT FROM DC TO THE CUSTOMERS. THE PROPOSED MODEL SELECTS SOME POTENTIAL PLACES AS DISTRIBUTION CENTERS IN ORDER TO SUPPLY DEMANDS OF ALL THE CUSTOMERS. SINCE THE PROBLEM IS CONSIDERED AS AN NP-HARD, IN THIS PAPER WE PROPOSE SEVERAL META-HEURISTICS TO SOLVE THE PROBLEM. FURTHERMORE, WE APPLY THE TAGUCHI EXPERIMENTAL DESIGN METHOD TO SET THE PROPER VALUES OF THE ALGORITHMS IN ORDER TO IMPROVE THEIR PERFORMANCES. FOR THE PURPOSE OF EVALUATING THE PERFORMANCES OF THE PROPOSED ALGORITHMS, VARIOUS PROBLEM SIZES ARE UTILIZED AND THE COMPUTATIONAL RESULTS OF THE ALGORITHMS ARE COMPARED WITH EACH OTHER. THE RESULTS SHOW THAT OUR MODEL CAN BE APPLIED AS AN EFFECTIVE TOOL FOR STRATEGIC PLANNING OF GREEN SUPPLY CHAINS.

IN THIS PAPER, A FUZZY MULTI-OBJECTIVE MODEL IS PRESENTED TO SELECT AND ALLOCATE THE ORDER TO SUPPLIER IN UNCERTAINTY CONDITIONS AND IN A MULTI-PERIOD, MULTI-SOURCE, AND MULTI-PRODUCT CASES AT TWO LEVELS OF SUPPLY CHAIN WITH PRICING CONSIDERATIONS. OBJECTIVE FUNCTIONS CONSIDERED IN THIS STUDY AS THE MEASURES TO EVALUATE THE SUPPLIERS ARE THE PURCHASE, TRANSPORTATION, AND ORDERING COSTS, TIMELY DELIVERING OR DEFERENCE SHIPMENT QUALITY OR WASTAGES WHICH ARE AMONGST MAJOR QUALITY ASPECTS, PARTIAL AND GENERAL COVERAGE OF SUPPLIERS IN RESPECT OF DISTANCE AND FINALLY SUPPLIERS' WEIGHTS MAKING THE PRODUCTS ORDERS AMOUNT MORE REALISTIC. DEFERENCE, WASTES, AND COVERAGE PARAMETERS IN THE MODEL ARE CONSIDERED AS UNCERTAIN AND RANDOM TRIANGULAR FUZZY NUMBER. SINCE THE PROPOSED MATHEMATICAL MODEL IS NP-HARD, WE APPLIED NON-DOMINATED SORTING GENETIC ALGORITHM (NSGA-II). TAGUCHI TECHNIQUE IS EXECUTED TO TUNE THE PARAMETERS OF ALGORITHM. THE RESULTS ARE ANALYZED BY QUANTITATIVE CRITERIA AND PARAMETRIC, AND NON-PARAMETRIC STATISTICAL ANALYSIS.

THE USE OF NON-STOCHASTIC MODELS SUCH AS FUZZY TIME SERIES FORECASTING MODELS FOR TIME SERIES ANALYSIS HAS ATTRACTED THE ATTENTION OF RESEARCHERS IN RECENT YEARS. AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODELS ARE ONE OF THE MOST IMPORTANT TIME SERIES MODELS USED IN FINANCIAL MARKET FORECASTING. RECENT RESEARCH ACTIVITIES IN TIME SERIES FORECASTING INDICATE THAT TWO BASIC LIMITATIONS DETRACT FROM THEIR POPULARITY FOR TIME SERIES FORECASTING: (1) ARIMA MODELS ASSUME THAT FUTURE VALUE OF A TIME SERIES HAVE A LINEAR RELATIONSHIP WITH CURRENT AND PAST VALUES AS WELL AS WITH WHITE NOISE. (2) ARIMA MODELS REQUIRE A LARGE AMOUNT OF HISTORICAL DATA IN ORDER TO PRODUCE ACCURATE RESULTS. FUZZY AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (FARIMA) MODELS ARE THE FUZZY IMPROVED VERSION OF THE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODELS, PROPOSED IN ORDER TO OVERCOME LIMITATIONS OF THE TRADITIONAL ARIMA MODELS; ESPECIALLY DATA LIMITATION, AND YIELD MORE ACCURATE RESULTS. EMPIRICAL RESULTS OF IRAN'S STEEL CONSUMPTION FORECASTING INDICATE THAT THE PROPOSED MODEL EXHIBIT EFFECTIVELY IMPROVED FORECASTING ACCURACY, SO IT CAN BE USED AS AN ALTERNATIVE MODEL TO STEEL CONSUMPTION FORECASTING, ESPECIALLY WHEN THE SCRIMPY DATA MADE AVAILABLE.

OVER THE LAST DECADE, THERE HAS BEEN AN INCREASED PRESSURE ON ENTERPRISES TO BROADEN THE FOCUS OF SUSTAINABILITY AND ACCOUNTABILITY IN BUSINESS PERFORMANCE BEYOND THAT OF FINANCIAL PERFORMANCE. BENEFITING FROM A PERFORMANCE MEASUREMENT SYSTEM IS AN INEVITABLE NECESSITY FOR ANY SUPPLY CHAIN TO DIRECT THE BUSINESS OPERATIONS TOWARDS THE MAXIMAL EFFICIENCY. DEMANDS FOR SUSTAINABILITY MANAGEMENT INCLUDES A VARIETY OF SOURCES, INCLUDING SOCIETAL MANDATES INCORPORATED INTO REGULATIONS, FEAR OF LOSS OF SALES, AND A POTENTIAL DECLINE IN REPUTATION IF A FIRM DOES NOT HAVE A TANGIBLE COMMITMENT TO SUSTAINABLE MANAGEMENT. THE SUSTAINABILITY PARADIGM CALLS FOR BALANCING ECONOMIC, ENVIRONMENTAL, AND SOCIAL NEEDS. THUS, THIS PAPER FOCUSES ON THE EVALUATION OF INDUSTRIAL SUPPLY CHAIN OPERATIONS, MAXIMIZING ECONOMIC RETURNS, MINIMIZING ENVIRONMENTAL IMPACTS, AND MEETING SOCIAL EXPECTATIONS. THE OBJECTIVE OF THIS WORK IS TO EXPAND THE UNDERSTANDING OF THE MEASUREMENT OF SUSTAINABILITY MANAGEMENT BY INTRODUCING A DATA ENVELOPMENT ANALYSIS (DEA) TECHNIQUE. BY EMPLOYING THE APPROACH OF CROSS EFFICIENCY, WE PRESENT A NEW MODEL TO MEASURE SUSTAINABILITY MANAGEMENT. THE NEW PROPOSED MODEL AND THE FINDINGS CONTRIBUTE TO THE BODY OF KNOWLEDGE IN SUSTAINABILITY MANAGEMENT AND ITS PERFORMANCE MEASUREMENT.

WITH THE MANUFACTURER WITH MASS CUSTOMIZATION PARADIGM EXTENDING ITS SCOPE INTO GLOBAL MANUFACTURING NETWORK, MODULE-BASED PRODUCT FAMILY CONFIGURATION AND SUPPLY CHAIN DESIGN SHOULD BE SIMULTANEOUSLY CONSIDERED. IN ORDER OF GLOBALLY DISTRIBUTED SUPPLY CHAIN NETWORK THE GREEN HOUSES GAS ESPECIALLY CARBON DIOXIDE EMISSION ARE INCREASED AND SHOULD BE CONSIDERED. IN THIS PAPER WE FORMULATES JOINT OPTIMIZATION OF PRODUCT FAMILY AND SUPPLY CHAIN CONFIGURATION WITH ENVIRONMENTAL CONSIDERATION. OBJECTIVE OF THE MODEL IS TO DETERMINE THE OPTIMAL BILLS OF MATERIALS THAT MINIMIZE THE ASSEMBLY AND SUPPLYING COSTS (FIXED AND VARIABLE) AT THE SAME TIME. TO DEMONSTRATE THE VIABILITY OF THE MODEL IT’S APPLIED ON A SMALL INSTANCE OF THE PROBLEM.

INTRODUCTION NOWADAYS IN COMPETITIVE INDUSTRIAL ENVIRONMENT, NECESSITY TO PRODUCTION IN HIGH VOLUME AND WITH HIGH QUALITY CAUSES CONDITIONS IN WHICH COMPANIES HAVE TO IMPLEMENT NEW PRODUCTION METHODS SUCH AS JUST IN TIME OR LEAN MANUFACTURING SYSTEMS. HOWEVER FLEXIBLE JOB SHOP PROBLEM IS A MODIFIED VERSION OF CLASSICAL JOB SHOP PROBLEM. IT HAS BEEN PROVED THAT THIS PROBLEM IS STRONGLY N-P HARD. SO SOLVING THIS PROBLEM IN REASONABLY COMPUTATIONAL TIME BY IMPLEMENTING THE EXACT SOLUTION METHODS IS ALMOST INTRACTABLE. SO IN RECENT YEARS MANY HEURISTIC AND META-HEURISTIC APPROACHES HAVE BEEN INTRODUCED AND DEVELOPED TO SOLVE THIS PROBLEM. HURINK ET AL (1994) [1] HAVE PRESENTED A TABU SEARCH METHOD FOR THIS PROBLEM...

OPTIMIZATION OF A SYSTEM IS EMPLOYED FOR MINIMIZING OR MAXIMIZING A KNOWN FUNCTION. THIS FUNCTION IS KNOWN AS A CRITERION IN WHICH ITS OPTIMIZATION RESULTS IN BETTER SYSTEM PERFORMANCE. PRESENT PAPER EVALUATES AND COMPARES THE PERFORMANCE OF FOUR WELL-KNOWN NATURE-INSPIRED OPTIMIZATION ALGORITHMS INCLUDING PARTICLE SWARM OPTIMIZATION (PSO), WHALE OPTIMIZATION ALGORITHM (WOA), WATER CYCLE ALGORITHM (WCA) AND CUCKOO SEARCH ALGORITHM (CSA). ALL THESE FOUR ALGORITHMS ARE CATEGORIZED IN META-HEURISTIC POPULATION -BASED OPTIMIZATION METHODS EXTRACTED FROM THE NATURE. IN CONTRARY TO THE GRADIENT-BASED METHODS, THIS BRANCH OF METHODS THAT HAS BEEN PAID MUCH ATTENTION BY RESEARCHERS IS NEEDLESS TO CALCULATE THE DERIVATIVES OF OBJECTIVE FUNCTION AND ALSO THE DESIGN CONSTRAINTS, AND IT STARTS THE SEARCH FROM A FEW NUMBER OF DESIGN. AFTER IMPLEMENTING THESE FOUR METHODS IN SOME UNCONSTRAINED OPTIMIZATION PROBLEMS, EACH METHOD’S PERFORMANCE IS OFFERED BASED ON THE REQUIRED TIME FRAMEWORK TO ACCESS THE OPTIMUM SOLUTION AND THE QUALITY OF PROBLEM SOLUTION.

TODAY, THE CHANGE IN ANY ORGANIZATION BEGINS WITH GRADUAL CHANGES TO FULLY IMPLEMENT. THIS RESEARCH IS A DESCRIPTIVE CROSS-SECTIONAL METHOD. THE RESEARCH ENVIRONMENT IS SARI CITY URBAN HEALTH CARE CENTERS. THE POPULATION CONSISTED OF 21 EMPLOYEES OF THIS CENTER. DATA WERE COLLECTED ON THE BASIS OF RESEARCHERS' QUESTIONNAIRE NEATNESS SYSTEM WITH FIVE AXES AND 25 QUESTIONS AND BASED ON LIKERT SCALE. SPSS SOFTWARE AND KOLMOGOROV–SMIRNOV TEST AND BINOMIAL AND ANOVA WERE USED FOR DATA ANALYSIS AND INTERPRETATION. ALL FIVE ITEM NEATNESS SYSTEM IS NORMAL BASED ON KOLMOGOROV–SMIRNOV TEST AND A SIGNIFICANT LEVEL OF 0.05. FINALLY, IN CLEANUP62%, ARRANGEMENT62%, CLEANING57%, STANDARDIZATION 47.5% AND CULTURE AXES28.5%, NEATNESS SYSTEM IMPLEMENTATION WERE ACHIEVED AND RESPECTIVELY. IT IS SUGGESTED THAT SPECIAL ATTENTION BE TO TRAINING EMPLOYEES AND MANAGERS AND PERFORM MONITORING AND MANAGEMENT OVERSIGHT TO ACHIEVE NEATNESS SYSTEM.

COST ESTIMATION IN THE SUPPLY CHAIN, IS ONE OF THE IMPORTANT ISSUES THAT EACH INSTITUTION OR A FACTORY IS FACING IN COST ESTIMATION COST MORE OR LESS OR EQUAL TO THE BUDGET.IN CASE OF EQUALLY OR LESS WE WILL NOT HAVE ANY TROUBLE BUT WE SHOULD TAKE MEASURES TO REDUCE THE COST OF CONDOLENCE. THE PURPOSE OF THIS ISSUE IS FIRST BUDGET ESTIMATION OF THE PROJECT AND THEN SHOWING GREATER THE COST OF THE ORIGINAL BUDGET USING BAYESIAN NETWORK THAT IN FOUR DIFFERENT SCENARIO OF THE COMPANY'S FINAL BUDGET IS CALCULATED.BAYESIAN NETWORKS, IS A VERY SIMPLE AND FRUITFUL SOLUTION TO SOLVE THE CASE HERE IN A ONE - WAY AUTHENTICATION METHOD AND THE COMPOSITION OF THE DIVIDED INTO TWO PHASES, AND WE REACHED TO THE ANSWER WITH THE SIMPLE METHOD OF SOLVING THE BUDGET.

THE LIFETIME OF A PRODUCT IS EXPECTED TO BE HIGH, THUS IT IS USUAL TO TERMINATE THE LIFE TEST AT A PREFIXED TIME. THIS TYPE OF TEST FOR EVALUATING THE LIFETIME OF A PRODUCT IS CALLED TRUNCATED LIFE TEST. IT IS ASSUMED THE LIFETIME OF A PRODUCT AS ITS QUALITY CHARACTERISTIC ANDTHE SEQUENTIAL SAMPLING PLAN IS APPLIED IN THE CONTEXT OF TRUNCATED LIFE TEST. IN THE SEQUENTIAL SAMPLING THE SAMPLES ARE SELECTED FROM THE LOT STAGE TO STAGE. IN EACH STAGE THE TOTAL NUMBER OF INSPECTED ITEM AND THE TOTAL NUMBER OF DEFECTIVE ITEMS TO THAT STAGE IS SPECIFIED AND BASED ON THEM IT IS DECIDED WHETHER TO CONTINUE SAMPLING, CEASE IT OR TAKE ANOTHER SAMPLE.FINALLY, BY ILLUSTRATING AN EXAMPLE THE APPLICATION OF THE SEQUENTIAL SAMPLING IS INDICATEDFOR THE TRUNCATED LIFE TEST.

GENERAL TYPES OF HYBRID ELECTRIC VEHICLES ARCHITECTURES ALONG WITH DIFFERENT CONTROL STRATEGIES ARE DESCRIBED IN THIS PAPER. THE SERIES, PARALLEL AND PARALLEL THROUGH THE ROAD ARCHITECTURES ARE INVESTIGATED AS THE GENERAL CONCEPTS FOR HEVS AND THE ADVANTAGES AND DISADVANTAGES OF THESE ARCHITECTURES WITH RESPECT TO COST AND CONTROL COMPLEXITY ARE ALSO COMPARED. ALTHOUGH THERE ARE DIFFERENT APPROACHES TO CONTROL HEVS IN ORDER TO ACHIEVE HIGHER FUEL EFFICIENCY AND LOWER EMISSIONS, BUT THE DIFFERENT CONTROL STRATEGIES HAVE BASIC LOGICS IN COMMON. IN THIS REGARD, THE GENERAL IDEA OF CONTROLLING THE HEVS FOR DIFFERENT TOPOLOGY IS DISCUSSED AND THE PERFORMANCE, FUEL CONSUMPTION AND EMISSIONS OF THE DIFFERENT HEV ARCHITECTURE IS CONTRASTED.

MANAGING INCOME IS A CONSIDERABLE DIMENSION IN SUPPLY CHAIN MANAGEMENT IN CURRENT ECONOMIC ATMOSPHERE. REAL WORLD SITUATION MAKES IT INEVITABLE NOT TO DESIGN OR REDESIGN SUPPLY CHAIN (SC). REDESIGN WILL TAKE PLACE AS COSTS INCREASE OR NEW SERVICES FOR CUSTOMERS’ NEW DEMANDS SHOULD BE PROVIDED. PRICING IS AN IMPORTANT FRAGMENT OF SC DUE TO TWO REASONS: FIRST, REPRESENTS REVENUE BASED EACH PRODUCT AND SECOND, BASED ON SUPPLY-DEMAND RELATIONS ENABLES SC TO PROVIDE DEMANDS BY MAKING SUITABLE CHANGES IN FACILITIES AND THEIR CAPACITIES. IN THIS STUDY, BENDERS DECOMPOSITION APPROACH USED TO SOLVE MULTI-PRODUCT, MULTI-ECHELON AND MULTI-PERIOD SUPPLY CHAIN NETWORK REDESIGN INCLUDING PRICE-SENSITIVE CUSTOMERS.

UNIVERSITY COURSE TIMETABLING PROBLEM (UCTP) IS A WELL-KNOWN CONSTRAINT SATISFACTION PROBLEM (CSP) PROBLEM THAT HAS EXPONENTIAL NUMBER OF SOLUTIONS BASED ON COURSE CONFLICTS, TEACHER’S EMPTY TIMES AND OTHER PARAMETERS. THIS IS A NP-HARD PROBLEM. SCHEDULING IS A MAJOR DEBATE ON PLANNING WHICH CAN BE USED IN TRAINS SCHEDULING, CLASSROOM SCHEDULING, TRAFFIC EVEN IN SCHOOLS AND UNIVERSITIES. THE SCHEDULING LEADS TO ORGANIZING TASKS AND REMOVING TASKS INTERFERENCE WHICH IS IMPORTANT. THE GOAL OF SOLVING UCTP IS SETTING TIMES FOR COURSES AND TEACHERS IN WEEKDAYS IN ORDER TO REACH MINIMUM COURSES CONFLICTS. IT IS ALSO IDEAL FOR TEACHERS TO HAVE JOINT DAYS FOR TEACHING IN THE LEAST WEEKDAYS. OF COURSE, SUBJECT TO THE RESTRICTIONS OF CLASSES AND TEACHERS PROGRAM THIS SCHEDULING IS VERY DIFFICULT. GENERALLY, EVOLUTIONARY ALGORITHMS (EA) ARE EFFICIENT TOOLS TO SOLVE THIS PROBLEM. THE FINAL TIMETABLING MUST BE OPTIMUM WHICH MEANS THAT THERE IS NO CONFLICTS IF POSSIBLE AND BEST SCHEDULING GENERATE FOR TEACHERS. IN THIS PAPER WE SOLVE THIS PROBLEM BASED ON GENETIC ALGORITHM AND IMPLEMENT THIS ALGORITHM WITH DEAP PYTHON BASED TOOLBOX ON RANDOM DATASET. THE IMPLEMENTATION RESULTS SHOW THAT GENETIC ALGORITHM IS EFFICIENT TOOLS THAT CAN CLOSE TO THE GLOBAL OPTIMUM POINT.

COMPETITIVE MULTI-AGENT SCHEDULING HAS ATTRACTED GROWING ATTENTION RECENTLY. IN THIS PAPER, TWO-AGENT SCHEDULING PROBLEM ON UNRELATED PARALLEL-MACHINE INVOLVING SETUP AND RELEASE DATE CONSIDERATIONS IS STUDIED. WE ALSO CONSIDER A FIXED NON-AVAILABILITY INTERVAL FOR THIS SCHEDULING PROBLEM SO THAT NO MACHINE CAN PROCESS JOBS IN A SPECIFIED NON-AVAILABILITY INTERVAL. EACH AGENT HAS ITS OWN SET OF JOBS AND OBJECTIVE FUNCTION, BUT BOTH SHARE THE SAME PROCESSOR. A MIXED INTEGER PROGRAMMING MODEL IS PROPOSED AND ITS GOAL IS TO MINIMIZE THE MAXIMUM COMPLETION TIME OF JOBS FROM THE FIRST AGENT SUBJECT TO A CONSTRAINT THAT THE OTHER AGENT’S MAXIMUM COMPLETION TIME CANNOT EXCEED A PRESCRIBED UPPER BOUND. FINALLY, NUMERICAL STUDIES ARE PERFORMED USING GAMS TO EXAMINE THE EFFECTIVENESS AND THE EFFICIENCY OF THE PROPOSED MODEL. ALSO, AN UPPER BOUND IS DEVELOPED TO INCREASE THE EFFICIENCY OF THE MODEL.

THE INITIAL STEP IN STATISTICAL ANALYSIS IS PARAMETER ESTIMATION. IN UNIVARIATE ANALYSIS, THE PARAMETERS MEAN AND STANDARD DEVIATION MUST BE ESTIMATED WHEN THEY ARE UNKNOWN. WHEN OUTLIERS EXIST IN DATA, USE OF SAMPLE MEAN RESULTS IN WEEK ESTIMATION. SO, ESTIMATORS WHICH ARE ROBUST TO THE PRESENCE OF OUTLIERS SHOULD BE USED. IN THIS WORK ROBUST M-ESTIMATOR FOR ESTIMATING THOSE PARAMETERS ARE USED. THE PERFORMANCE OF THESE ROBUST ESTIMATORS IN PRESENCE OF OUTLIERS AND THEIR EFFECTS ON PROCESS CAPABILITY INDICES ARE STUDIED. THE RESULTS INDICATE THAT THE PROPOSED ROBUST CAPABILITY INDICES PERFORM MUCH BETTER THAN THE EXISTING PROCESS CAPABILITY INDICES.

THIS PAPER CONSIDERS A LINEAR PROGRAMMING PROBLEM INVOLVING RANDOM INTERVAL COEFFICIENTS. A RANDOM INTERVAL PROGRAMMING MODEL IS PRESENTED BY EXTENDING THE EXPECTATION MODEL OF STOCHASTICPROGRAMMING. THE ORIGINAL PROBLEM INVOLVING RANDOM INTERVAL PARAMETERS IS TRANSFORMED INTO A DETERMINISTIC EQUIVALENT PROBLEM USING THE PROPOSED MODEL. THE EFFICIENCY OF THE PROPOSED MODELIS CALLIED BY A NUMERICAL EXAMPLE.

IN MULTI-ECHELON SUPPLY CHAINS, THE PRODUCT MADE BY MANUFACTURER WITH INITIAL PRODUCTION COSTS. THEN TO REACH THE END CONSUMER, IT WILL PASS FROM DIFFERENT LEVELS OF THE SUPPLY CHAIN. EACH MEMBER OF THE CHAIN IS IN MUTUAL COMMUNICATION WITH UPSTREAM AND DOWNSTREAM. THEREFORE, IN ORDER TO ACHIEVE THE BEST QUALITY AND THE LOWEST PRODUCTION COST, A LARGE NUMBER OF COMPANIES HAS CONCURRENT COLLABORATION WITH MANY SUPPLIERS. IN THIS PAPER, WE CONSIDER A WHOLESALE-PRICE CONTRACT WHERE DEMAND OF THE PRODUCT IS DEPENDENT TO SELLING PRICE WITH LINEAR DEMAND CURVE. WE OBTAIN THE AMOUNT OF OPTIMAL PROFIT FOR EACH MEMBER OF TWO-ECHELON AND THREE-ECHELON SUPPLY CHAIN AND CONSEQUENTLY DETERMINE THE OPTIMAL ORDERING PRICING DECISIONS FOR PARTNERS. FINALLY, IT IS PROVED THAT BY INCREASING THE NUMBER OF ECHELONS UNDER WHOLESALE PRICE CONTRACT, THE CHANNEL'S EFFICIENCY DECREASES DRAMATICALLY.

SUPPLIER SELECTION AND IN ADDITION, OPTIMAL ORDER ALLOCATIONS ARE THE MOST STRATEGIC AND TACTICAL DECISION PROBLEMS IN SUPPLY CHAIN MANAGEMENT. IN A CLOSED-LOOP SUPPLY CHAIN NETWORK, THERE ARE BOTH FORWARD AND REVERSE SUPPLY CHAINS. CLOSED-LOOP SUPPLY CHAIN SYSTEMS REFER TO PROCESSES RELATED TO THE REUSE, RESALE, REPAIR, REFURBISHING AND RECYCLING PRODUCTS. THE ROLE OF SUPPLIERS’ PERFORMANCE IN CLOSED-LOOP SUPPLY CHAIN SYSTEMS IS CRUCIAL TO ACHIEVE THE GOALS OF QUALITY, COST, SERVICE AND DELIVERY OF A SUPPLY CHAIN. THEREFORE, THIS ARTICLE PRESENTS AN OPTIMIZATION MODEL TO MAXIMIZE THE TOTAL PROFIT, MINIMIZE TOTAL DEFECTIVE PARTS, TOTAL LATE DELIVERED PARTS, ECONOMIC RISK FACTORS OF THE SUPPLIERS AND ALSO MINIMIZE TOTAL CARBON-DIOXIDE RELEASED FROM MANUFACTURING AND REFURBISHING PLANTS TO BE CLOSE TO THE GREEN SUPPLY CHAIN. ON THE OTHER HAND, THE BEST SUPPLIERS AND OPTIMAL NUMBER OF PARTS AND PRODUCTS WILL BE OBTAINED. THIS MULTI-OBJECTIVE OPTIMIZATION MODEL HAS BEEN SOLVED BY GENETIC ALGORITHM ON MATLAB SOFTWARE.

THIS PAPER PRESENTS FUZZY LOWER AND UPPER PROBABILITIES FOR THE RELIABILITY OF PARALLEL SYSTEMS. ATTENTION IS RESTRICTED TO PARALLEL SYSTEMS WITH EXCHANGEABLE COMPONENTS. IN THIS PAPER WE CONSIDER THE PROBLEM OF THE EVALUATION OF SYSTEM RELIABILITY BASED ON THE NONPARAMETRIC PREDICTIVE INFERENTIAL (NPI) APPROACH, IN WHICH THE DEFINING THE PARAMETERS OF RELIABILITY FUNCTION AS CRISP VALUES IS NOT POSSIBLE AND PARAMETERS OF RELIABILITY FUNCTION ARE DESCRIBED USING A TRIANGULAR FUZZY NUMBER. FORMULA OF A FUZZY RELIABILITY FUNCTION AND ITS A-CUT SET ARE PRESENTED. THE FUZZY RELIABILITY OF STRUCTURES IS DEFINED ON THE BASIS OF FUZZY NUMBER. FURTHERMORE, THE FUZZY RELIABILITY FUNCTIONS OF PARALLEL SYSTEMS DISCUSSED. FINALLY, SOME NUMERICAL EXAMPLES ARE PRESENTED TO ILLUSTRATE HOW TO CALCULATE THE FUZZY RELIABILITY FUNCTION AND ITS A-CUT SET. IN OTHER WORDS, THE AIM OF THIS PAPER IS PRESENT A NEW METHOD TITLED FUZZY NON-PARAMETRIC PREDICTIVE INFERENCE FOR THE RELIABILITY OF PARALLEL SYSTEMS.

ALTHOUGH IN RECENT YEARS MANY META-HEURISTIC METHODS HAVE BEEN PRESENTED, MOST OF THEM ARE BASED ON POPULATION AND BEAR MANY STEPS, SEVERAL PARAMETERS AND HARD TO UNDERSTAND AND CODE. SO, THE RESEARCHERS USUALLY USE THE OLD ALGORITHMS INSTEAD OF RECENT ONES. CONTRARY TO PREVIOUS WORK, THIS PAPER AIMS TO DEVELOP A SIMPLE, INTELLIGENT AND NEW SINGLE-SOLUTION ALGORITHM THAT HAS FOUR MAIN STEPS AND JUST THREE SIMPLE PARAMETERS TO TUNE. SOCIAL ENGINEERING OPTIMIZATION (SEO) STARTS WITH TWO INITIAL SOLUTIONS, DIVIDED INTO ATTACKER AND DEFENDER. THE ATTACKER OBTAINS THE RULES OF SOCIAL ENGINEERING TECHNIQUES TO REACH DESIRED ITS GOALS. THE BASIS OF THE ALGORITHM IS TO HOW AN ATTACKER ATTACKS TO DEFENDER BY FOUR DIFFERENT ASSOCIATED TECHNIQUES. FINALLY, THE PROPOSED SEO IS APPLIED TO SOLVE SOME BENCHMARK FUNCTIONS AND AN ENGINEERING PROBLEM AND ALSO THE RESULTS SHOW ITS SUPERIORITY IN COMPARISON WITH OTHER WELL-KNOWN AND RECENT META-HEURISTIC.

DECISION-MAKING ABOUT THE LOCATION OF THE MUNICIPAL SOLID WASTE (MSW) SYSTEM’S FACILITIES IS ONE OF THE CHALLENGING ISSUES IN AN URBAN AREA BECAUSE OF ITS CONSIDERABLE IMPACTS ON ECONOMY, ECOLOGY, AND THE ENVIRONMENT. ALSO, SINCE SUCH STRATEGIC PROBLEMS ARE TAINTED WITH GREAT DEGREE OF UNCERTAINTY, THIS STUDY PROPOSES A BI-OBJECTIVE FUZZY MATHEMATICAL PROGRAMMING MODEL FOR DESIGN OF A MSW MANAGEMENT SYSTEM BY CONSIDERING BOTH ECONOMICAL AND ENVIRONMENTAL ASPECTS. A VERSION OF ROBUST POSSIBILISTIC PROGRAMMING (RPP) APPROACH I.E. RPP-II IS USED TO HANDLE THE UNCERTAIN PARAMETERS OF THE PROBLEM. APPLICABILITY OF THE PROPOSED MODEL IN PRACTICE IS ILLUSTRATED THROUGH THE TEHRAN MSW SYSTEM WHERE DETERMINE THE LOCATION AND ALLOCATION OF TRANSFER STATIONS AS WELL AS THE APPROPRIATE WASTE COMPACTING TECHNOLOGY LEVELS FOR THESE FACILITIES.

PUBLIC HEALTH, NOWADAYS, HAS BEEN RECEIVED A SIGNIFICANT AMOUNT OF GROSS DOMESTIC PRODUCT (GDP) AND PRECISELY INVESTIGATION OF THE COST MANAGEMENT THROUGH PUBLIC HEALTH PROGRAMS STILL REMAINS AS A CHALLENGING ISSUE. HOWEVER, THERE STILL REMAINS A NEED FOR DEVELOPING A COMPREHENSIVEHEALTH PERFORMANCE EVALUATION TOOL. IN THIS PAPER, A NEW APPLICATION OF EARNED VALUE MANAGEMENT (EVM) IS PRESENTED DEALING WITH THIS ISSUE WITH A FOCUS ON IMMUNIZATION PLANNING. IMPLEMENTATION OF THE OBTAINED RESULTS REVEAL THAT THE PRESENTED FRAMEWORK CAN BE DEVELOPED AS A UNIVERSAL PERFORMANCE EVALUATION TOOL IN PUBLIC HEALTH SECTOR. BY USING EVM TECHNIQUE, NOT ONLY HEALTHCARE PROGRAMS CAN BE EVALUATED AFTER THE EXECUTION OF THE PROGRAM, BUT ALSO THEY CAN BE MONITORED DURING THE EXECUTION STAGE. THEREFORE, THESE HEALTH OPERATIONS' RESULTS CAN BE PREDICTED EASILY. USING CONTENT ANALYSIS TECHNIQUES, THE FRAMEWORK CAN DEAL WITH QUALITATIVE CLINICAL ATTRIBUTES AND TURN THEM INTO QUANTITATIVE AND MEASURABLE DATA. A REAL-LIFE IMPLEMENTATION ON PEDIATRIC IMMUNIZATION IS MENTIONED FORPRACTICAL VERIFICATION.

THIS PAPER PRESENTS THE DEVELOPMENT OF DYNAMIC SCHOOL BUS ROUTING PROBLEM TO DESIGN TRANSPORT SYSTEMS. IN A REAL WORLD THE USING PRIVATE CARS ARE RIVAL FOR PUBLIC TRANSPORTATION SYSTEMS. SO THE SHORTCOMINGS OF THESE SYSTEMS WILL LEAD TO AN INCREASE IN THE DEMAND FOR USING PRIVATE CARS. THIS ISSUE WILL LEAD TO PROBLEMS SUCH AS INCREASED TRAFFIC AND URBAN POLLUTION. HENCE, A NEW DYNAMIC BI-LEVEL MODEL IS PRESENTED FOR DESIGNING SUCH A SYSTEM. IN THIS MODEL, THE PUBLIC TRANSPORT SYSTEM DESIGNER AS A HIGH-LEVEL DECISION MAKER IS TO LOCATE APPROPRIATE BUS STOPS AND BUSES’ ROUTE. ANY DECISIONS MADE AT THE UPPER LEVEL MODEL WILL BE FOLLOWED BY STUDENTS' REACTION AT THE LOWER LEVEL.TO SOLVE THIS PROBLEM A HYBRID SA-EX-TS APPROACH HAS BEEN PROPOSED BASED ON A LOCATION-ALLOCATION-ROUTING (LAR) STRATEGY. THE RESULTS SHOWED GOOD PERFORMANCE OF SOLUTION APPROACH PROPOSED IN REASONABLE TIME.

SURGICAL THEATER IS ONE OF THE MOST SENSITIVE AND MOST EXPENSIVE HOSPITAL SOURCES THAT A HIGH PERCENTAGE OF HOSPITAL ADMISSIONS ARE RELATED TO IT. THEREFORE, EFFICIENT PLANNING AND SCHEDULING OF THE OPERATING ROOMS IS NECESSARY TO GUARANTEE OPTIMAL USE OF RESOURCES, TIMELY SURGERY AND INCREASE PATIENTS’ SATISFACTION. THEREFORE, IN THIS PAPER, THE WEEKLY PLANNING AND SCHEDULING OF THE OPERATING ROOMS IS ADDRESSED TO MINIMIZE THE WAITING TIME OF ELECTIVE PATIENTS, OVERUTILIZATION AND UNDERUTILIZATION COST OF OPERATING ROOMS AND THE SUM OF SURGERIES’ COMPLETION TIME. WE TAKE INTO ACCOUNT THE AVAILABLE HOURS OF OPERATING ROOMS AND THE SURGEONS, LEGAL CONSTRAINTS, THE SKILL LEVEL OF SURGEONS AND PRIORITY OF PATIENTS IN THE MODEL. A REAL-LIFE EXAMPLE IS PROVIDED TO DEMONSTRATE THE EFFECTIVENESS AND APPLICABILITY OF THE MODEL AND IS SOLVED USING Ε-CONSTRAINT METHOD IN GAMS SOFTWARE. THEN, DATA ENVELOPMENT ANALYSIS IS EMPLOYED TO OBTAIN THE PREFERRED SOLUTION AMONG THE PARETO SOLUTIONS ACHIEVED BY Ε-CONSTRAINT METHOD, WHICH IS COMPARED TO THE SCHEDULE USED IN THE HOSPITALS.

IN THIS ARTICLE, WE FIRST GIVE SOME DEFINITIONS AND GENUINE DIFFERENCES BETWEEN HARDWARE AND SOFTWARE. WE ALSO DISCUSS A STATISTICAL MODEL USED HERE AND PROVE SOME BASICALLY PROPERTIES. THEN, WE PROVIDE DIFFERENT RELIABILITY PROPERTIES OF OUR CASE STUDY IN A STEP BY STEP MANNER NUMERICALLY AND GRAPHICALLY. WE ALSO USE THE CASRE PROGRAM AS A TOOL IN SOFTWARE RELIABILITY ESTIMATION IN SOME STEPS.

RESEARCH STUDIES HAVE PROVEN THAT RCM, IF PLANNED PROPERLY, CAN BE EFFECTIVE IN IMPROVING EQUIPMENT RELIABILITY AT REDUCED COSTS. THIS PAPER PRESENTS A REVIEW OF RCM LITERATURE WITH EMPHASIS ON DIFFERENT MAINTENANCE APPROACHES AND RCM MODELLING. WE FOCUS THIS REVIEW ON IMPORTANT ASPECTS OF THE RCM, SUCH AS IMPLEMENTATION METHODOLOGY AND ITS OBSTACLES. SINCE THE MODELLING CHOICE FOR THE EXECUTION PROCESS GREATLY INFLUENCES RCM SUCCESS, THIS PAPER PRESENTS PROMOTION SOLUTIONS FOR MAINTENANCE SYSTEMS. THIS RESEARCH PROVIDES USEFUL REFERENCES FOR RCM MANAGEMENT PROFESSIONALS AND RESEARCHERS WORKING ON RCM MODELLING AND OPTIMIZATION. IT CONCLUDES THAT MOST RECENTLY STUDIES FOCUS ON MATHEMATICAL MODELLING AND THE MOST RELEVANT CHOICES WHICH NEED TO BE PRIORITIZED COULD BE DEVELOPED BASED ON AHP.

THIS PAPER STUDIES THE EFFECT OF COMPETITION FOR TWO COORDINATING SUPPLY CHAINS. EACH SUPPLY CHAIN HAS ONE MANUFACTURE AND TWO COMMON RETAILERS. THERE IS COMPETITION AT BOTH MANUFACTURER AND RETAILER LEVELS. THE TWO MANUFACTURERS PRODUCE TWO SUBSTITUTABLE PRODUCTS WITH DIFFERENTIATE BRANDS. THUS, THEY COMPETE ON BRAND AND SELL THEIR PARTICULAR PRODUCTS BY THE TWO COMMON RETAILERS WHICH COMPETE ON ORDERING AND PRICING POLICIES. WE OBTAIN THE OPTIMAL PAIR OF PRICING AND ORDERING POLICIES FOR THE SUPPLY CHAIN AND ALL OF FOUR INDIVIDUAL MEMBERS. THEN USING THE CONCEPTS OF COOPERATIVE GAME THEORY FOR COORDINATION ANALYSIS WE SHOW THAT ACHIEVING COORDINATION UNDER WHOLESALE-PRICE CONTRACT PROVIDE NON-PROFITABLE MANUFACTURERS. THUS, THE MANUFACTURERS SHOULD ESTABLISH A STACKELBERG-GAME WITH PARTIAL CHANNEL EFFICIENCY.

THE NP-CHART IS USED TO MONITOR THE NUMBER OF NONCONFORMING ITEMS IN A SAMPLE. THE PERFORMANCE OF THE NP-CHART IN PHASE II DEPENDS ON THE ACCURACY OF ESTIMATED PARAMETER IN PHASE I. DESPITE THE FACT THAT TAKING LARGE SAMPLE SIZES ENSURE THE PERFORMANCE OF ESTIMATED PARAMETER CHARTS, IT CAN BE IMPRACTICAL FOR ATTRIBUTE CONTROL CHARTS. RECENTLY, THE PERFORMANCE OF TRADITIONAL C-CHART AND NP-CHART WITH SOME ADJUSTMENTS HAVE BEEN STUDIED. IN PRACTICE, HIGH QUALITY PROCESSES WITH VERY LOW RATE OF NONCONFORMITIES ARE OFTEN OBSERVED. THE TRADITIONAL CONTROL CHARTS SUFFER A SERIOUS INACCURACY IN CONTROL LIMITS SPECIFICATION IN THIS WAY. HAVING ALL THIS IN MIND, THIS PAPER PRESENTS A NEW NP-CHART BASED ON SIMPLE ADJUSTMENTS DERIVED FROM CORNISH-FISHER EXPANSIONS TO IMPROVE SUCH INACCURACY WITH THE APPLICATION OF BOOTSTRAP. BASED ON THE CONDITIONAL IN-CONTROL AVERAGE RUN LENGTH (ARL0), THEIR PERFORMANCES ARE COMPARED THROUGH A SIMULATION STUDY.

IN THE STUDY OF THE RELIABILITY OF SYSTEMS IN RELIABILITY ENGINEERING, IT HAS BEEN DEFINED SEVERAL MEASURES IN THE RELIABILITY AND SURVIVAL ANALYSIS LITERATURE. THE RELIABILITY FUNCTION, THE MEAN RESIDUAL LIFETIME AND THE HAZARD RATE ARE HELPFUL TOOLS TO ANALYZE THE MAINTENANCE POLICIES AND BURN-IN. IN THIS PAPER, WE CONSIDER A NETWORK CONSISTING OF 𝑛 COMPONENTS HAVING THE PROPERTY THAT THE NETWORK HAS TWO STATES UP AND DOWN (CONNECTED AND DISCONNECTED). SUPPOSE THAT THE NETWORK IS SUBJECT TO SHOCKS THAT EACH MAY CAUSE THE COMPONENT FAILURES. WE FURTHER SUPPOSE THAT THE NUMBER OF FAILURES AT EACH SHOCK FOLLOWS A TRUNCATED BINOMIAL DISTRIBUTION AND THE PROCESS OF SHOCKS IS NONHOMOGENEOUS POISSON PROCESS. THIS PAPER INVESTIGATES THE RELIABILITY FUNCTION, THE MEAN RESIDUAL LIFETIME AND THE HAZARD RATE OF THE NETWORK UNDER SHOCK MODEL. AN EXAMPLE AND ILLUSTRATIVE GRAPH IS ALSO PROVIDED.

THE AIM OF THIS PAPER IS DEFINING AN OPTIMAL MODEL FOR A RETAILER WHO USES A 100% SCREENING PROCESS TO REVEAL DEFECTIVE ITEMS WHICH ARE RECEIVED FROM THE SUPPLIER. THE DEMAND RATE IS LOWER THAN THE SCREENING RATE AND THE DEFECTIVE ITEMS WILL BE SENT TO A REPAIRING SHOP TO BE REPAIRED. ACCORDING TO THE FIXING RATE, THE PRODUCTS WILL BE SENT BACK TO THE RETAILER AFTER A WHILE. DURING THE FIXING PROCESS THE RETAILER MAY FACE SHORTAGES. THE GOAL IS FINDING THE ORDERING AMOUNT TO MAXIMIZE THE RETAILER'S PROFIT DURING THE PLANNING HORIZON. THE MATHEMATICAL MODEL WILL BE DESCRIBED AND RENEWAL-REWARD THEOREM WILL BE USED TO SOLVE THE PROPOSED MODEL CONSIDERING A NUMERICAL EXAMPLE.

NOWADAYS, IN GLOBAL FREE MARKET, THIRD-PARTY LOGISTICS PROVIDERS (3PLS) ARE BECOMING INCREASINGLY IMPORTANT. HENCE, THIS STUDY AIMS TO DEVELOP THE FREIGHT CONSOLIDATION AND CONTAINERIZATION PROBLEM, WHICH CONSISTS OF LOADING ITEMS INTO CONTAINERS AND THEN SHIPPING THESE CONTAINERS TO DIFFERENT WAREHOUSE FROM THEY ARE DELIVERED TO THEIR FINAL DESTINATIONS. IN ORDER TO HANDLE THE PROPOSED PROBLEM, THIS RESEARCH IS NOT ONLY USED THE TRADITIONAL AND RECENT ALGORITHMS, BUT ALSO THE TWO NEW HYBRIDIZED METHODS ARE INTRODUCED IN ORDER TO STRENGTH OF ADVANTAGES OF RECENT ONES. IN THIS REGARD, THIS STUDY CONSIDERS THE TWO IMPORTANT PHASES IN META-HEURISTIC TO DEVELOP NEW ONES. BESIDES, TAGUCHI EXPERIMENTAL DESIGN METHOD IS UTILIZED TO SET AND ESTIMATE THE PROPER VALUES OF THE ALGORITHMS’ PARAMETERS TO IMPROVE THEIR PERFORMANCE. FOR THE PURPOSE OF PERFORMANCE EVALUATION OF THE PROPOSED ALGORITHMS, VARIOUS PROBLEM SIZES ARE EMPLOYED AND THE COMPUTATIONAL RESULTS OF THE ALGORITHMS ARE COMPARED WITH EACH OTHER. FINALLY, THE IMPACTS OF THE RISE IN THE PROBLEM SIZE ON THE PERFORMANCE OF THE PROPOSED ALGORITHMS ARE INVESTIGATED.

THIS PAPER STUDIES THE AMBULANCE ROUTING PROBLEM IN DISASTER SITUATIONS WHEN A LARGE NUMBER OF INJURED PEOPLE FROM VARIOUS LOCATIONS REQUIRE TO RECEIVE TREATMENT AND MEDICAL AID. IN SUCH CIRCUMSTANCES, MANY PEOPLE SUMMONING THE AMBULANCE AT THE SAME TIME BUT THE CAPACITY AND NUMBER OF EMERGENCY VEHICLES ARE NOT SUFFICIENT ENOUGH TO VISIT ALL THE PATIENTS IMMEDIATELY. THEREFORE, A CRUCIAL PART IS TO MANAGEMENT THE FLEET OF AMBULANCES SO AS TO MITIGATE HUMAN SUFFERING. FOR THIS REASON, WE CONSIDERED THREE DIFFERENT CATEGORIES OF PATIENTS WITH VARIOUS REQUIREMENTS. ALSO THE SUPPORT AMBULANCES ARE SEGMENTED TO VARIOUS CLASSES BASED ON THEIR CAPABILITIES. A MATHEMATICAL FORMULATIONS IS PRESENTED TO OBTAIN ROUTE PLANS WITH THE AIM OF MINIMIZING THE LATEST SERVICE COMPLETION TIME AMONG THE PATIENTS. SINCE, DISASTERS CAUSE MAJOR DAMAGES TO LIFELINE INFRASTRUCTURES SUCH AS REFUELING-STATIONS, SO PROVIDED MODEL DESIGNS THE AMBULANCES ROUTES IN SUCH WAY THAT OVERCOME TO DIFFICULTIES THAT EXIST AS A RESULT OF LIMITED REFUELING. PROPOSED MIP PROBLEM IS THEN IMPLEMENTED BY GAMS SOFTWARE. FINALLY, A SENSITIVITY ANALYSIS IS PROVIDED TO EVALUATE THE RELATIONSHIP BETWEEN THE PROBLEM STRUCTURES AND ACHIEVED SOLUTIONS.

IN TODAY’S COMPETITIVE WORLD, A BEWILDERING AMOUNT OF DATA IS BEING GENERATED. BY UTILIZING APPROPRIATE TECHNIQUES, THE KNOWLEDGE HIDDEN WITHIN THE DATA CAN BE UNCOVERED AND USED AS A TOOL FOR QUALITY IMPROVEMENTS IN A BUSINESS. DATA MINING PRESENTS A COLLECTION OF EFFICIENT TOOLS FOR KNOWLEDGE ELICITATION IN DATA WAREHOUSES. MOBARAKEH STEEL COMPANY, AS ONE OF MAJOR INDUSTRIES IN IRAN, HAS A SIGNIFICANT IMPACT ON MARKET AND ECONOMY BOTH IN TERMS OF EXTENT AND SCALE. FROM THIS POINT OF VIEW, IT HAS ADVANTAGES OVER SIMILAR COMPANIES IN THE REGION. ONE OF THE MOST IMPORTANT PRODUCTION LINES IN THE COMPANY IS THE GALVANIZED STEEL COILS PRODUCTION LINE WITH A CAPACITY OF 20, 000 TONS PER YEAR. IN THIS RESEARCH, DATA MINING TECHNIQUES ARE APPLIED ON A DATABASE OF GALVANIZED STEEL COILS DEFECTS IN ORDER TO EXTRACT THE GOVERNING RULES. HAVING THE 10 CHEMICAL ANALYSIS PARAMETERS OF THE PRODUCTS DURING 2012 TO 2015, THE ASSOCIATED RULES ARE OBTAINED. THE DATA USED IN THIS STUDY ARE OBTAINED FROM THE DATABASE PROVIDED FROM THE QUALITY CONTROL DEPARTMENT IN THE MOBARAKEH STEEL COMPANY. THE RULES ARE SHOWN TO BE EFFECTIVE IN MODELLING THE KNOWLEDGE WITHIN THE DATA. IN ADDITION, IT IS SHOWN THAT NOT ALL THE DEFECTS IN THE PRODUCTS ARE ROOTED IN THE METALLURGIC PROPERTIES RECORDED IN THE DATABASE. THIS CALLS FOR A DEEPER INVESTIGATION FOR FURTHER STUDY THE EFFECTS OF OTHER FACTORS SUCH AS HUMAN FACTORS AND EQUIPMENT.

THE FUNDAMENTAL FUNCTION OF A CELLULAR MANUFACTURING SYSTEM (CMS) IS BASED ON DEFINITION AND RECOGNITION OF A TYPE OF SIMILARITY AMONG THE PARTS THAT MUST BE PRODUCED IN A PLANNING PERIOD. CELL FORMATION (CF) AND CELL MACHINE LAYOUT DESIGN ARE TWO IMPORTANT STEPS IN IMPLEMENTATION OF THE CMS. THIS PAPER REPRESENTS A NEW MATHEMATICAL NONLINEAR PROGRAMMING MODEL FOR DYNAMIC CELL FORMATION THAT EMPLOYS THE RECTILINEAR DISTANCE NOTION TO DETERMINE THE LAYOUT IN THE CONTINUOUS SPACE. IN THE PRESENTED MODEL, THE OBJECTIVE FUNCTION ACCURATELY CALCULATES THE COSTS OF INTER AND INTRA-CELL MOVEMENTS OF PARTS AND CALCULATES THE COST OF A CELL RESTRUCTURE. DUE TO THE PROBLEM COMPLEXITY, THE PRESENTED MATHEMATICAL MODEL IS CATEGORIZED IN NP-HARDNESS; THUS, A GENETIC ALGORITHM (GA) IS USED FOR SOLVING THIS PROBLEM. COMPARING THE RESULTS FROM THE GA AND THE RESULTS FROM SOLVING A LINEAR MODEL THROUGH LINGO SPECIFIES THAT SOLVING THE PRESENTED MODEL ACCURATELY FOR MORE THAN FOUR MACHINES IN A LOGICAL TIME IS IMPOSSIBLE.

IN THIS PAPER, WE CONSIDER COORDINATING THE SUPPLY CHAIN SCHEDULING PROBLEM AND BATCH DELIVERY IN A FLOW SHOP MANUFACTURING SYSTEM. THE PROBLEM IS TO MINIMIZE THE SUM OF WEIGHTED TARDINESS PENALTIES AND THE DELIVERY COSTS OF THE JOBS, WHERE THE JOBS ARE DELIVERED IN BATCHES. A MIXED INTEGER PROGRAMMING MODEL IS PROPOSED FOR THE PROBLEM. IN ADDITION, A PARTICLE SWARM OPTIMIZATION ALGORITHM IS USED FOR SOLVING THE LARGE-SCALE INSTANCES. TO EXPLORE AND TO LOCATE THE ALGORITHM IN A BETTER NEIGHBORHOOD, A LOCAL SEARCH IS PRESENTED. TO VERIFY THE DEVELOPED MODEL AND EVALUATE THE PERFORMANCE OF ALGORITHM AGAINST THE EXACT SOLUTION, A COMMERCIAL SOLVER IS USED. FURTHERMORE, THE INFLUENCE OF THE DIFFERENT PARAMETERS AND ASSUMPTIONS OF THE PROPOSED MODEL ARE DISCUSSED.

THIS PAPER DEALS WITH COORDINATING SUPPLIER DEVELOPMENT PROGRAMS IN A TWO-ECHELONSUPPLY CHAIN WHICH IS FORMULATED ASA CONTINUOUS TIMEOPTIMAL CONTROL MODEL. DRAWING UPON ADVANCED INGREDIENTS OF DIFFERENTIAL AND POISSON GEOMETRY, A NOVEL METHODOLOGY IS PRESENTED FOR THE OPTIMAL CONTROL PROBLEM BY REFORMULATING AND CONVERTING THE HAMILTON-JACOBI-BELLMAN PARTIAL DIFFERENTIAL EQUATION (PDE) TO A REDUCED HAMILTONIAN SYSTEM, SO THAT THE EXACT OPTIMAL SOLUTION OF THE CONTROL PROBLEM CAN BE OBTAINED, INSTEAD OF NUMERICAL ESTIMATION. THE PROPOSED METHODOLOGY IS APPLIED TO THE PROBLEM OF COORDINATING SUPPLIER DEVELOPMENT IN A SUPPLIER-MANUFACTURER SUPPLY CHAIN TO FIND THE EXACT OPTIMAL SOLUTION. THE ANALYTICAL SOLUTIONTO THE PROBLEMIS OBTAINED BASED ON THE PROPOSED METHOD ANDA NUMERICAL EXAMPLE IS PRESENTEDTO FURTHER VALIDATE ITSAPPLICABILITY AND SUPERIORITY. THE PROPOSED METHODOLOGY CAN BE ALSO APPLIED TO CONTROL PROBLEMSIN OTHER OPTIMIZATION FIELDS.

WE CONSIDER THE PRODUCTION POSSIBILITY SET WITH N PRODUCTION UNITS SUCH THAT THE FOLLOWING FOUR PRINCIPLES THAT GOVERNS: INCLUSION OBSERVATIONS, CONCEIVABILITY, IMMENSITY AND CONVEXITY. OUR GOAL IS TO ESTIMATE THE OUTPUT OF A NEW PRODUCTION UNIT WITH AMOUNT OF INPUT IS SPECIFIED. INITIALLY, WE FIND THE INTERVAL CHANGES OF EACH INPUTS AND OUTPUTS AND THEN PARTITIONING EACH INTERVAL WITH FUZZY NUMBERS. WE USE EACH OF THE POSSIBLE TO PRODUCE WITH SPECIFIC INPUTS AND OUTPUTS THE FUZZY IF-THEN RULES AND ESTIMATE THE AMOUNT OF OUTPUTS WITH MAMDANY METHOD IN FUZZY INFERENCE MECHANISM. FINALLY, WE PRESENT AN EXAMPLE.

MEDICAL ERRORS ARE CONSIDERED AS ONE OF THE MAJOR CHALLENGES OF THE HEALTH THROUGHOUT THE WORLD SYSTEM AND IMPOSE MANY COSTS ON SOCIETY EVERY YEAR. THE LOSSES THAT CAUSED BY MISMANAGEMENT OF THESE HAZARDS ARE NOT ONLY FOR THE PATIENT, THESE ERRORS CAN AFFECT THE LOSS OF GOOD PHYSICIANS AND HOSPITALS REPUTATION. THREATS OF MEDICAL ERRORS IN THE HEALTHCARE SYSTEM, PREDISPOSE THE MOVEMENTS AND EFFORTS TO MINIMIZE THE STATISTICS OF THESE ERRORS, MORTALITY AND DISABILITY. THE AIM OF THIS STUDY IS TO PROVIDE A SYSTEMIC MODEL TO ANALYZE THE DYNAMICS OF THE HEALTHCARE SYSTEM RISKS TO ELIMINATE OR REDUCE THE DAMAGES OF SERVICES. IN THIS PAPER, WE COULD ADDRESS TO IDENTIFY FACTORS INFLUENCING THE ADVERSE EVENTS DUE TO MEDICAL ERRORS WITH USING SYSTEM DYNAMICS (SD) APPROACH AND SHOWS THEIR IMPACT ON OUR HEALTHCARE SYSTEM AND CLINICAL ERRORS. ACCORDING TO THE PROPOSED MODEL, CREATING A SAFETY CULTURE IN THE HEALTH SECTOR, USING INDICATORS OF OVERALL PERCEPTION OF SAFETY, NON-PUNITIVE RESPONSE TO ERROR, ORGANIZATIONAL LEARNING, RESPONSIBILITY, SUPERVISION AND TEAM COMMUNICATIONS PLAY AN IMPORTANT ROLE IN REDUCING ADVERSE EVENTS IS DUE TO MEDICAL ERRORS, IN ADDITION TO INCREASING KNOWLEDGE AND SKILLS OF STAFF THROUGH TRAINING ON THE JOB CAN ALSO HAVE A SIGNIFICANT IMPACT IN REDUCING THESE INCIDENTS. USING A SYSTEMIC APPROACH IN DEALING WITH THE PROBLEM OF MEDICAL ERRORS LED TO SUPPORT OF PHYSICIANS AND WILL RESULT ENCOURAGING THEMSELVES TO EXPRESS THE ERRORS. EXPRESSED THE ERRORS WILL LEAD TO THE SYSTEM DETECTION AND WILL HELP THE ERROR ANALYSIS AND PREVENTIVE MEASURES

IN THIS RESEARCH A JOBSHOP SCHEDULING PROBLEM WITH AN ASSEMBLY STAGE IS STUDIED. THE OBJECTIVE FUNCTION IS TO FIND A SCHEDULE WHICH MINIMIZES COMPLETION TIME FOR ALL PRODUCTS. AT FIRST, A LINEAR MODEL IS INTRODUCED TO EXPRESS THE PROBLEM. THEN, IN ORDER TO CONFIRM THE ACCURACY OF THE MODEL AND TO EXPLORE THE EFFICIENCY OF THE ALGORITHMS, THE MODEL IS SOLVED BY GAMS. SINCE THE JOB SHOP SCHEDULING PROBLEM WITH AN ASSEMBLY STAGE IS CONSIDERED AS A NP-HARD PROBLEM, A HYBRID ALGORITHM IS USED TO SOLVE THE PROBLEM IN MEDIUM TO LARGE SIZES IN REASONABLE AMOUNT OF TIME. THIS ALGORITHM IS BASED ON GENETIC ALGORITHM AND PARALLEL VARIABLE NEIGHBORHOOD SEARCH. THE RESULTS OF THE PROPOSED ALGORITHM ARE COMPARED WITH THE RESULT OF GENETIC ALGORITHM. COMPUTATIONAL RESULTS SHOWED THAT FOR SMALL PROBLEMS, BOTH HGAPVNS AND GA HAVE APPROXIMATELY THE SAME PERFORMANCE. AND IN MEDIUM TO LARGE PROBLEMS HGAPVNS OUTPERFORMS GA.

OPTIMIZATION IS CONSIDERED AS AN ART TO DISCOVER THE BEST SOLUTION AMONG THE AVAILABLE ONES. META-HEURISTIC ALGORITHMS ARE ONE TYPE OF THE RANDOM ALGORITHMS USED FOR FINDING THE OPTIMIZED SOLUTIONS. SINCE THE SIMPLICITY OF THE CONCEPTS AND THE ACCEPTABLE PERFORMANCE IN A WIDE RANGE OF ISSUES, THIS GROUP OF ALGORITHMS HAS LATELY BEEN THE CENTER OF CONCENTRATIONS. THE PRESENT STUDY INVESTIGATES AND COMPARES THE META-HEURISTIC OPTIMIZATION ALGORITHMS SUCH AS ARTIFICIAL BEE COLONY (ABC), GRAVITATIONAL SEARCH ALGORITHM (GSA), GENETICS (GA), AND FIREFLY ALGORITHMS (FA) FOR TRUSS STRUCTURES WITH A FOCUS ON ITS WEIGHT OPTIMIZATION.

IN MIXED MODEL ASSEMBLY LINES, SEVERAL PRODUCTS WITH HIGH SIMILARITY ARE SIMULTANEOUSLY PRODUCED ON AN ASSEMBLY LINE AS PER THE SEQUENCE WITHOUT ANY ADDITIONAL SETUP TIMES BETWEEN THE MODELS. THIS PAPER CONCENTRATES ON MIXED MODEL ASSEMBLY LINE BALANCING AND SEQUENCING TYPE-II PROBLEM. THE PROBLEM HAS SOME PARTICULAR FEATURES SUCH AS U-SHAPED WORKSTATIONS AND SETUP TIMES BETWEEN TWO CONSECUTIVE TASKS IN DYNAMIC PERIODS WHEREIN EACH PERIOD ALSO AFFECTS THE FLOWING PERIOD. THIS RESEARCH INTENDS TO REDUCE CYCLE TIME AND INVENTORY COSTS. TO THIS END, A NON-DOMINATED SORTING GENETIC ALGORITHM (NSGA-II) IS USED TO SOLVE THE PROBLEM. SMALL SCALES OF THE PROBLEM ARE SOLVED USING BOTH NSGA-II AND GAMS SOFTWARE TO EVALUATE THE EFFECTIVENESS OF NSGA-II, AND THE OBTAINED OUTCOMES ARE COMPARED. THE COMPUTATIONAL RESULTS INDICATE THAT THE NSGA-II IS CAPABLE OF PROVIDING HIGH-QUALITY SOLUTIONS FOR SMALL SCALES OF THE PROBLEM. FINALLY, CONCLUSION AND FUTURE RESEARCH ARE PROVIDED.

QUALITY IN THE CONSTRUCTION INDUSTRY IS A FUNCTION OF A WIDE RANGE OF FACTORS AMONG WHICH, THOSE DEPENDING ON THE RESIDENTS’ VIEWPOINT ARE OF A HIGH IMPORTANCE. THIS STUDY PRESENTS A MODEL FOR EVALUATING THE PERFORMANCE OF MASS-CONSTRUCTED RESIDENTIAL BUILDINGS IN IRAN IN TERMS OF SATISFACTION OF RESIDENTS, BASED ON AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS), AND AIMS TO PROVIDE APPLICABLE RESULTS. THE MEASUREMENT OF THE QUALITY OF BUILDINGS AND EXPECTATIONS OF THE OCCUPANTS IS DONE THROUGH COLLECTING AND ANALYZING DATA USING QUESTIONNAIRES. RESULTS SHOW THAT THE SATISFACTION LEVEL WITH REGARD TO SECURITY AND PRIVACY IN BUILDINGS ARE OF A HIGHER IMPORTANCE THAN OTHER ASPECTS OF THE BUILDINGS AND THE MOST IMPORTANT FACTORS DETERMINING SATISFACTION WERE THE TYPE, LOCATION AND AESTHETIC APPEARANCE OF THE BUILDINGS, WHICH MUST BE CONSIDERED IN DESIGNING BUILDINGS. ACCESS TO ENERGY RESOURCES IN BUILDINGS WITH REGARD TO RESOURCE ALLOCATION BY GOVERNMENT NEEDS TO BE MODIFIED, TOO.

WE DESIGN A TREE-STRUCTURED POWER DISTRIBUTION NETWORK CONSIDERING OPTIMAL CABLE SIZING. A MIXED-INTEGER PROGRAMMING MODEL IS FORMULATED TO MINIMIZE THE TOTAL COST IN THE NETWORK. THE AIM IS TO DETERMINE THE OPTIMAL SIZES OF CABLES SO THAT THE LOCATION-ALLOCATION COST IS MINIMIZED. DISTRIBUTION LINES IN POWER NETWORK MUST BE DESIGNED BASED ON MAXIMUM ALLOWABLE ELECTRICAL FLOW IN CABLES, ALLOWABLE LENGTH OF CABLES, MAXIMUM ALLOWABLE VOLTAGE DROPS AND BALANCE OF LOAD. WE USE INFORMATION BASED ON RELATIONSHIP AMONG RATES OF ELECTRICAL FLOW AND CABLES SIZES CONSIDERING VOLTAGE DROPS AND LENGTH RESTRICTIONS. WE APPLY MINIMUM SPANNING TREE TECHNIQUE TO CREATION A NETWORK WITH MINIMUM NUMBER OF ARCS AND NO CLOSED LOOP SUCH AS ALL THE NODES COVERED. A CASE STUDY IN TEHRAN POWER DISTRIBUTION COMPANY IN IRAN IS CONDUCTED TO ILLUSTRATE THE VALIDITY OF PROPOSED MODEL.

HLP (HUB LOCATION PROBLEM) TRIES TO FIND LOCATIONS OF HUB FACILITIES AND ASSIGNMENT OF NODES TO EXTENDED FACILITIES. HUBS ARE VERY CRUCIAL AND THEIR INACCESSIBILITY IMPRESSES ON NETWORK WHOLE LEVELS. IN THIS PAPER WE ARE MAKING EFFORT TO EITHER MAXIMIZE THE AVERAGE RELIABILITY OR MINIMIZE TOTAL COST. TO MODEL AND SOLVE THE PROBLEM, THE FUZZY MULTI-OBJECTIVE PROGRAMMING APPROACH HAS BEEN PRESENTED. EVENTUALLY, A SET OF TEST PROBLEMS ARE PRESENTED AND THE NUMERICAL CONSEQUENCES ARE ANALYZED AND WE INSPECTED THEM BY PLOTTING.

DESIGNING SUPPLY CHAIN ACCORDING TO REAL-WORLD SITUATIONS IS CONSTANTLY ONE OF THE KEY ISSUES OF STRATEGIC PLANNING IN THE SUPPLY CHAIN. IN THIS ARTICLE, FOR THE FIRST TIME, A NEW MATHEMATICAL MODEL FOR SUPPLY CHAIN NETWORK DESIGN ISSUE HAS BEEN PROPOSED BY TAKING THE THREE-LEVEL SINGLE-SOURCE RISK-POOLING, THE INVENTORY IN DISTRIBUTION CENTERS WITH UNCERTAIN DEMAND, AS WELL AS THREE-DIMENSIONAL TRANSPORT IN A SUPPLY CHAIN NETWORK SYSTEM. UNLIKE PREVIOUS WORKS DONE IN THIS AREA, AND TO BE CONSISTENT WITH THE ACTUAL SITUATION, THE POSSIBILITY OF USE OF SEVERAL TYPES OF VEHICLES, FOR EACH STAGE EXISTS. UNCERTAIN CUSTOMERS’ DEMAND HAS BEEN CONSIDERED AND LIMITATIONS, SUCH AS CAPACITY OF VEHICLES ARE CONSIDERED. THIS ISSUE HAS BEEN FORMULATED AS A NON- LINEAR PROGRAMMING MODEL. FINALLY, TO VALIDATE THE MODEL, THE COMPUTATIONAL RESULTS OBTAINED FROM THE SIMULATION OF REAL-WORLD SOLUTIONS TO REAL-LIFE EXAMPLES, USING A RELATED SOFTWARE IS SUGGESTED.

PROPOSING DISCOUNT OFFERS FOR PRODUCTS' PRICES USUALLY DIRECTLY INFLUENCES ON THE PROCESS OF DISTRIBUTING AND SELLING PRODUCTS. THE FIXED CHARGE TRANSPORTATION PROBLEM (FCTP) IS A DEPLOYMENT OF THE CLASSICAL TRANSPORTATION PROBLEM IN WHICH A FIXED COST IS INCURRED, INDEPENDENT OF THE AMOUNT TRANSPORTED, ALONG WITH A VARIABLE COST THAT IS PROPORTIONAL TO THE AMOUNT SHIPPED. SINCE THE PROBLEM IS CONSIDERED AS AN NP-HARD, IN THIS PAPER WE PROPOSE A WELL-KNOWN METAHEURISTIC TO SOLVE THE FCTP WITH DISCOUNT SUPPOSITION ON BOTH FIXED AND VARIABLE CHARGES. IN ADDITION, TWO MODELS WITH ALL-UNITS DISCOUNT AND INCREMENTAL DISCOUNT IS FIRSTLY PROPOSED IN THIS STUDY TO APPLY THE DISCOUNT MECHANISM. ALSO, AS THE PREVIOUS RESEARCHERS MAINLY USED SPANNING TREE-BASED AND PRIORITY-BASED REPRESENTATIONS, WE USED BOTH METHODS IN METAHEURISTIC AND COMPARED THE RESULTS. FURTHERMORE, WE APPLY THE TAGUCHI EXPERIMENTAL DESIGN METHOD TO SET THE PROPER VALUES OF ALGORITHM IN ORDER TO IMPROVE ITS PERFORMANCE. FINALLY, COMPUTATIONAL RESULTS METAHEURISTIC WITH DIFFERENT ENCODING APPROACHES, BOTH IN TERMS OF THE SOLUTION QUALITY AND COMPUTATION TIME, ARE INVESTIGATED IN DIFFERENT PROBLEM SIZES.

ATTRACTIVENESS OF FACILITIES HAS A GREAT ROLE ON THE SUCCESS OF PREVENTIVE HEALTHCARE FACILITIES. IN CONTRAST TO SICK PEOPLE, THE PUBLIC SHOULD SUFFICIENTLY BE MOTIVATED TO PARTICIPATE IN PREVENTIVE PROGRAMS. ATTRACTIVENESS CAN BE MODELED AS A FUNCTION OF DISTANCE AND CONGESTION DELAYS IN THE FACILITIES. IN THIS PAPER, WE STUDY A PREVENTIVE HEALTHCARE NETWORK DESIGN PROBLEM WITHIN A FRAMEWORK OF CASE STUDIES IN IRAN, SO AS TO MAXIMIZE THE PARTICIPATION OF PUBLIC IN PREVENTIVE HEALTHCARE PROGRAMS. THE CONCEPT OF UTILITY OF CUSTOMERS, DEFINED AS THE SURPLUS OF THE CUSTOMERS’ WILLINGNESS TO PAY OVER THE TRAVEL DISTANCE AND CONGESTION DELAYS, IS CONSIDERED IN THE CONSTRAINT SET. IN THE CASE STUDIES, THE NEEDED DATA IS EXTRACTED FROM GEOGRAPHICAL INFORMATION SYSTEM TO FIND OUT THE ACCURATE DISTANCES AMONG THE NODES OF THE NETWORK.

LOCATION AREA IS ONE OF THE MOST IMPORTANT RESEARCH AREAS IN DECISION-MAKING DUE TO THE WIDELY USED. HUB LOCATION AS A TYPE OF LOCATION PROBLEM HAS MANY APPLICATIONS SUCH AS TRANSPORTATION AND TELECOMMUNICATION SYSTEMS. THE HUB LOCATION PROBLEM (HLP) INVOLVES FINDING THE LOCATION OF HUBS AND ALLOCATES THE OTHER NODES TO THEM. A SIGNIFICANT ISSUE THAT MORE SHOULD BE NOTED THAT IT IS ALWAYS MINIMIZING COST IS NOT A PERFECT SOLUTION FOR THE SURVIVAL. THEREFORE, OTHER PARAMETERS SUCH AS PRICE PLAY SIGNIFICANT ROLE IN THE SURVIVAL OF THE ORGANIZATION. THEREFORE, IN THIS ARTICLE, WE CONSIDER PROFIT AT INCOMPLETE HUB LOCATION AND ROUTING PROBLEM OVER THE INCOMPLETE NETWORKS. WE USE TWO TYPE DATASETS. FIRST, IRANIAN ROAD NETWORK (IRN) AND SECOND, AUSTRALIA POST (AP). WE RUN THE MODEL FOR DIFFERENT VALUES OF A AND G ON SOFTWARE CPLEX 12.5 AND OBSERVE NUMBER OF HUBS, NUMBER OF HUB NODES, NUMBER OF HUB LINKS AND SPOKE LINKS. THE RESULTS SHOW THAT THE LOCATION OF HUBS IS NOT USUALLY ALTERED BY CHANGING IN THE PRICE. MOREOVER, THE NUMBER OF SPOKE LINKS MAY BE CHANGED BY INCREASING THE PRICE.

IN THIS PAPER AN EFFECTIVE METAHEURISTIC ALGORITHM INSPIRED BY TREES COMPETITION FOR ACQUIRING LIGHT AND FOODS IS PROPOSED. DIVERSIFICATION AND INTENSIFICATION PHASES AND THEIR TRADEOFF ARE DETAILED IN THE PAPER. ALSO, THE PROPOSED APPROACH IS VERIFIED BY USING SOME OF BENCHMARK FUNCTIONS COMMONLY USED IN THIS RESEARCH AREA. TO ASSISTANCE THE TGA'S EFFICIENCY, SOME OF WELL-KNOWN OPTIMIZATION ALGORITHMS SUCH AS GENETIC ALGORITHM (GA) AND PARTICLE SWARM OPTIMIZATION (PSO) ARE EMPLOYED. TGA AND THESE MENTIONED ALGORITHMS ARE COMPARED IN SOME OF USED MATHEMATICAL BENCHMARK IN THIS AREA. FINALLY, THE OBTAINED RESULTS SHOW THAT THE TGA HAVE A GOOD REACTION FOR SOLVING OPTIMIZATION PROBLEMS.

A FLEXIBLE JOB SHOP SCHEDULING PROBLEM WITH ASSEMBLY OPERATIONS AND SEQUENCE DEPENDENT SETUP TIME IS STUDIED IN THIS PAPER. IN THIS PROBLEM, AT THE FIRST STAGE, THE PARTS ARE PROCESSED IN A FLEXIBLE JOB SHOP SYSTEM AND THEN THEY ARE ASSEMBLED IN AN ASSEMBLY STAGE TO PRODUCE PRODUCTS. SETUP TIME IS NEEDED WHEN A MACHINE STARTS PROCESSING THE PARTS OR IT CHANGES ITEMS. AT FIRST, A LINEAR MODEL IS INTRODUCED TO EXPRESS THE PROBLEM. THE OBJECTIVE IS TO MINIMIZE THE COMPLETION TIME OF ALL PRODUCTS. THEN SINCE THE PROBLEM IS NP-HARD, A HYBRID METAHEURISTIC ALGORITHM IS PRESENTED. THE PROPOSED ALGORITHM IS CALLED A HYBRID PARTICLE SWARM OPTIMIZATION WITH A PARALLEL VARIABLE NEIGHBORHOOD SEARCH ALGORITHM (HPSOPVNS). FINALLY, THE NUMERICAL EXPERIMENTS ARE USED TO EVALUATE AND VALIDATE THE PERFORMANCE OF THE MATHEMATICAL MODEL AND PROPOSED ALGORITHM. THE COMPUTATIONAL RESULTS SHOW THAT HYBRID ALGORITHM ACHIEVES BETTER PERFORMANCE THAN PARTICLE SWARM OPTIMIZATION ALGORITHM (PSO).

TODAY, WASTE MANAGEMENT IS MORE IMPORTANT THAN IN THE PAST, BECAUSE WITH THE GROWING POPULATION AND LARGE-SCALE PRODUCTION IN FACTORIES, CONSUMPTION PATTERNS HAVE BEEN CHANGED AND HIGHER WASTE IS PRODUCED. THIS PAPER PROVIDES A COMPREHENSIVE REVIEW ON PAPERS THAT INCLUDING OF MATHEMATICAL MODELING IN THE FIELD OF URBAN WASTE. MATHEMATICAL MODELS IN PEER-REVIEWED ARTICLES, IS INCLUDING OF LOCATION THE RECYCLING AND DISPOSAL CENTERS, LOCATION THE TRANSFER STATIONS AND ROUTING OF VEHICLES FOR GARBAGE COLLECTION. THERE ARE SEVERAL OBJECTIVES SUCH AS SOCIAL, ECONOMIC AND ENVIRONMENTAL. FINALLY, BY DISCOVERING UNEXPLORED AREAS OF RESEARCH, SUGGESTIONS ARE PRESENTED FOR THE FUTURE RESEARCH.

IN THIS PAPER, CONSIDER THE ISSUE OF COORDINATION AND PRICING IN SINGLE-PERIOD GREEN SUPPLY CHAIN. IT IS BASED ON MARKET DEMAND AND IN THIS MARKET GREEN PRODUCT AND NON-GREEN PRODUCTS CO-EXIST WITH AND SUBSTITUTE EACH OTHER, AND EXAMINE THE RESULTS FOR TWO PRODUCTION MODES IN COOPERATIVE GAME AND NON-COOPERATIVE GAME. THEORETICAL ANALYSIS SHOW THAT DIFFERENT PRODUCTION COSTS WILL CAUSE THE MANUFACTURER DECISION FOR CHOICE OF PRODUCTION MODE WHEN CONSUMERS HAVE DIFFERENT EVALUATIONS OF THE PRODUCTS. FURTHERMORE, THE RESULTS INDICATE THAT SYSTEM PERFORMANCE IN COOPERATIVE GAME IS EVIDENTLY BETTER THAN THAT IN NON-COOPERATIVE GAME. THE COOPERATIVE PRICING STRATEGY COORDINATED BY RUBINSTEIN BARGAINING MODEL CAN REALIZE THE PARETO OPTIMIZATION OF SUPPLY CHAIN SYSTEM PROFIT AND MEMBER PROFITS UNDER DIFFERENT PRODUCTION MODES. FINALLY, THE NUMERICAL EXAMPLE IS PROVIDED TO VALIDATE THE RESULTS.