Year:2006 | Volume:40 | Issue:4 (98)|Papers Count:14

This paper introduces a business process simulation (BPS) model of a purchasing process in a research-manufacturing company. Then, this model is used to introduce and evaluate several improvement and business process re-engineering (BPR) models. The users of the purchasing management verify that the goals of a BPR model are to create a process-oriented approach in order to reduce purchasing process cycle time, faster customer response time, and lower cost. The conceptual model of the business process is developed by an integrated definition for function modeling (IDEF0). The associated process times are collected by standard time study and then analyzed by a statistical analysis. In addition, the computer simulation model of the process is developed by the Visual SLAM software, in which this model is verified and validated by F-test and t-test. Two scenarios are proposed according to the BPR concepts showing more efficiency than other scenarios. The first model is compromised by using only information technology (IT) and information engineering. In the second model, the process is designed by using the Davenport's approach as process designing as well as using organizational, human resource, and IT enablers. Finally, the proposed models are analyzed using the trade-offs analysis and then the BPR model by using the enablers is chosen as the best model.

In the last few decades, a vehicle routing problem (VRP) is one of the significant issues in order to increase efficiency and productivity in logistic and transportation systems. In this problem, there is a set of vehicle located in one or more depots to serve a set of customers with a deterministic demand. In this paper, a new mathematical model is introduced to maximize the customer satisfaction by minimizing the fleet cost, routes cost, and tardiness penalty of violating soft time windows. Soft time windows in serving customers are considered outside of hard time windows. This model belongs to a class of NP-hard problems that cannot be optimally solved within reasonably computational time. Thus, an efficient metaheuristic method based on simulated annealing (SA) is proposed. To improve the quality of SA, 1-Opt and 2-Opt genetic operators are introduced. A number of test problems are solved by this proposed SA in order to show its efficiency. The associated computational results are compared with the results obtained by the Lingo 6 software package.

In this paper, a stochastic and uncertain flow shop scheduling problem is considered. Processing times are not known exactly, so they are estimated as intervals. Thus, the processing time of job i on machine j is a fuzzy set that is the possibility distribution of the processing time. Due date is a random variable defined for make span. In certain models, there are two major criteria; make span and lateness. In stochastic models, they are expected value of make span and lateness probability. The main problem in stochastic flow shops is to estimate the criteria that exactly defined. In this study, we will consider the probability of lateness fuzzy event. We demonstrate a mathematical method for evaluating the criteria. Finally, a near-optimal solution as a sequence will be obtained by a heuristic method. 

In this paper, a probabilistic continuous review inventory model is developed for deteriorating items. The model is developed under conditions of stochastic demands and no shortages in which both lead time and order quantity are treated as decision variables. We concentrate on lead time as a deterministic variable which is made endogenous through an “expediting factor” τ, the constant of proportionality between the reduced lead time and ordinary time. For models, we determine the expected cost per unit time then numerical examples are given. Additionally sensitivity analyses are conducted with respect to the various cost parameter ranges and remarks are made for further researches.

This paper considers the problem of scheduling parallel machines for split jobs to minimize the total tardiness. Accepting a new job, each machine needs to be set up and the setup times depend on the sequence of jobs. To solve the above problem, a new approach is suggested and a number of theorems are provided and proved regarding resource planning and job sequencing for the given problem in hand. Then, the proposed algorithm is verified and evaluated with a number of test problems. The associated results are analyzed and compared with the results obtained by the Lingo software.

In this paper, we consider the effect of rework of defective items on the economic batch quantity (EBQ). In the classical EBQ model, it is assumed that the products produced during each cycle are all non-defective. However in practice, there are many situations in which a certain amount of defective products are produced during each cycle. In this paper, we assume that in each production cycle when the normal production ends the rework of defective items starts immediately after a non-zero set up time for the rework process. In deriving the mathematical model, other than the costs considered in the classical EBQ, we consider the inspection cost, rework and holding costs of defective items, set up cost for rework, and the cost of waiting time of defective items for rework. Then, we obtain the optimal batch quantity which minimizes the sum of the above costs.

A project evaluation and review technique (PERT) is a method for estimating the project completion time. It holds some assumptions in the level of activity and in the level of network of activities. PERT calculates the mean and variance of each activity time based on activity level assumptions and calculates the project completion time according to the computed mean and variance of each activity. This paper presents a new method for estimating the mean and variance of activity time based on two parameters estimated by the expert's knowledge and has no further assumptions about parameters of the Beta distribution. The proposed method is compared with the existing ones based on statistical comparison (i.e., paired t-test & variance analysis). The absolute average error of the new method with a wrong acceptance error is equal to (first kind of error) 1% which is less than the absolute average error of all existing ones in the subjective PERT approximation.

More and more companies use organizational self-assessment to identify and improve their competitive positions in order to cope with an ever-changing environment. The use of the EFQM Excellence Model as a framework for organizational self-assessment has spread too many companies. Nowadays, one of the main objectives for each unit in an organization, its survival, present competitions, and in this global village is to increase the customer satisfaction. Thus, this issue has its effect on every organizational competition. The aim of this paper is to explore the causal structure of the Customer Result criteria in the EFQM Excellence Model. First, a framework for the relationship between the above criteria is developed based on theoretical arguments of criteria and sub criteria in the above model. Then in customer satisfaction, three famous models consisting of European Customer Satisfaction Index (ECSI), American Customer Satisfaction Index (ACSI), and Kristensen & Martensen’s Customer Satisfaction Model are also developed. These three models demonstrate same causal model for the Customer Result criteria in the EFQM Excellence Model. These models are included and discussed about this subject. By considering the above models, four criteria consisting of the Processes (the 5th one), the Society Results (the 8th one), the People Results (the 7th one), and the Partnerships & Resources (the 4th one) affect on the Customer Results criteria (the 6th one). This criterion affects on the Key Performance Results criteria (the 9th one).

This paper presents a heuristic method to find out a good tour for the asymmetric traveling salesman problem. At first, the proposed approach uses the normalized cost matrix to construct a tour by choosing the cities in such a way that it avoids having to go to very high cost (distance or time) cities later on. In order to improve further the size of this tour, it uses a developed tour improvement method. To evaluate its performance, the cost normalization algorithm for the solution of the linear assignment problem as well as the proposed method have been coded in C++ and many problems with up to 500 cities have been tested. The solved problems include a number of asymmetric random problems and all the benchmark asymmetric traveling salesman problems. The results indicate that the method returns a very good tour on all tested problems.

Supplier Selection is one of the prime functions of companies’ logistic management. Due to the importance of selecting appropriate vendors in companies’ performance, this area has been under consideration and many conceptual and analytical models have been developed for solving this problem. In this paper, the proposed model is an integrated model based on a supplier selection process in a real-world situation. Firstly, using Case-Based Reasoning (CBR) approach, which is a method for solving problems by making the use of previous similar situations, a short list of suppliers which passes the basic requirements of buyer is prepared. Secondly, based on detailed information inquired from the pre-selected suppliers, a Multi Objective Mathematical Programming (MOMP) model is established to assess the candidate suppliers. The output identifies the final list of selected suppliers and the quantity of orders allocated among them. Finally, it is shown how an integrated model based on the CBR and a Mathematical Programming model can be used for identifying and evaluating of suppliers and allocating orders among the selected ones.

This paper focuses on Case-Based Reasoning (CBR) approach, which is a method for solving problems by making the use of previous similar situations, and it has been recommended for the Vendor Selection Problem (VSP) recently. In this study, a fuzzy set theory is used to incorporate the vague nature of some vendor selection criteria. In the suggested model, a linear membership function of a fuzzy type is employed to quantify the vagueness in decision parameters. Furthermore, for increasing the accuracy of retrieving a suitable vendor from among available alternatives in the case-base, Fuzzy TOPSIS has been proposed for final evaluation of retrieved vendors.

In this paper, inflation rates (internal and external) are time-dependent and demand rate is inflation-dependent. Deteriorating items are considered and shortages are allowed. The inventory level is described by differential equations over time horizon and the present value method is used. A numerical example is given to explain the results. Six particular cases, which follow the main problem, are discussed and the results are compared with the main model by using numerical examples.