Journal of Operational Research in its Applications
Year:2024 | Volume:21 | Issue:2|Papers Count:8

2Currently, there are many methods to solve the linear fractional programming problem under non-negative fuzzy variables. Due to the flaws and limitations of these methods, they cannot be used to solve the fully fuzzy fractional linear programming (FFLFP) problem in which all variables and parameters are fuzzy. This paper intends to propose an efficient method for the FFLFP problem with trapezoidal fuzzy numbers, which converts unequal constraints into equal constraints by adding auxiliary variables and solves the problem without using ranking. Finally, the proposed method will be compared with other methods by implementing it practically in some examples and the degree of desirability of this method will be measured in terms of the simplicity of operation and the accuracy of the results. Also, a real example of a wood producing company will also be examined and will be resolved.

2In today's world, each system needs more facilitates to use them for improving according to speed of nowadays’ changes. Most activities use own proprietary programs to act as independent one and to control own through systems. Supply chains contain various levels that can be used to supply primal materials for changing them to required products and finally present them to customers via different systems. Integrated manufacturer- provided planning is one of important issues in supply chain. Considering it with a special competition can be considered less in recent literatures. In this paper, a mathematical model is proposed for an integrated manufacturer-provided planning based on competition in a multi-levels supply chain. The suggested model is formulated by four objective functions and related constraints for a two-period and multi-product with vertical competition in the supply chain. The model is solved using augmented epsilon constraint method. The results of a numerical example present the advantages and potential applications of proposed model.

2This paper investigates the problem of heterogeneous vehicle routing with a time window to simultaneously pick up and deliver products to customers. In this method, vehicles with different speeds and capacities have been used to deliver products. In this research, mathematical programming models have been developed to minimize the routing costs of heterogeneous vehicles by considering the time windows of the collection cost until the delivery of the product from its authorized centers to the customer. Due to the NP-hard nature of the routing problem on a large scale, heuristic and meta-heuristic algorithms have been used to solve this problem. Based on the obtained results, three meta-heuristic methods of iterative local search ILS, combined genetic algorithm, and automatic moving grid search algorithm (AGS) have been used. The calculation results show that the lowest cost has been achieved by sending 67 different vehicles to pick up and deliver multiple products to the customer by dividing the city of Tehran into 16 districts. The results of the research show that with the dispatch and optimal routing of this number of vehicles, the cost of the logistics system will decrease by 38.58% compared to the current situation. Based on the computational results, the proposed algorithm can optimally route heterogeneous vehicles under the time window constraint for simultaneous delivery of products.

2The complexities of the decision space and planning of organizations due to the presence of a large amount of variables, data and information lead managers to use valid group and multi-criteria decision making techniques. Although there have been many studies and researches in the field of job satisfaction, a comprehensive study with multi-dimensional indicators has been neglected until now, and this study has taken a step in this direction to solve this gap and deficiency. This research has been done with the aim of prioritizing management strategies in order to strengthen the job satisfaction of Dezful municipality employees. The current research is practical in terms of its purpose, and in terms of its nature and form, it is descriptive and survey. The number of samples examined in this research is 22 people and the sampling method is snowball method. The decision matrix questionnaire tool was used to collect research data. In order to analyze the data and determine the priority of the strategy, the taxonomy decision making technique has been used. According to the results of the present study, among the six indicators in the evaluation of job satisfaction strategies, the interest to work index was identified as the most important index with 27.2% of the total 100% job satisfaction. Also, among the 12 job satisfaction strategies, the employee job security strategy is the first priority, which means that managers in organizations should pay special attention to the job security category in order to create job satisfaction, which causes interest be usedKeywords: job satisfaction, management strategies, motivation, municipal employees, multi-criteria decision making, taxonomy technique.

2Due to the sensitivity of patients in the intensive care unit, the most important issue in medical services is the appropriate timing for allocating resources, especially the intensive care unit (I.C.U) to patients to complete the treatment process and has always been the main challenge for all patients in the I.C.U. In this study, a model for scheduling tasks and personnel planning of I.C.U department with the aim of maximizing the profit from the number of patients served in these centers is presented. On the other hand, the process of profitability of hospitals from the I.C.U (number of patients treated) requires proper planning and scheduling of treatment activities under the uncertainty of work and the use of fuzzy logic is one of the new approaches to control these uncertainties. The results of scheduling and planning executive activities before and after attending the I.C.U ward showed that in a case study, the number of patients receiving services increased by an average of 17%.Due to the sensitivity of patients in the intensive care unit, the most important issue in medical services is the appropriate timing for allocating resources, especially the intensive care unit (I.C.U) to patients to complete the treatment process and has always been the main challenge for all patients in the I.C.U. In this study, a model for scheduling tasks and personnel planning of I.C.U department with the aim of maximizing the profit from the number of patients served in these centers is presented. On the other hand, the process of profitability of hospitals from the I.C.U (number of patients treated) requires proper planning and scheduling of treatment activities under the uncertainty of work and the use of fuzzy logic is one of the new approaches to control these uncertainties. The results of scheduling and planning executive activities before and after attending the I.C.U ward showed that in a case study, the number of patients receiving services increased by an average of 17%.Due to the sensitivity of patients in the intensive care unit, the most important issue in medical services is the appropriate timing for allocating resources, especially the intensive care unit (I.C.U) to patients to complete the treatment process and has always been the main challenge for all patients in the I.C.U. In this study, a model for scheduling tasks and personnel planning of I.C.U department with the aim of maximizing the profit from the number of patients served in these centers is presented. On the other hand, the process of profitability of hospitals from the I.C.U (number of patients treated) requires proper planning and scheduling of treatment activities under the uncertainty of work and the use of fuzzy logic is one of the new approaches to control these uncertainties. The results of scheduling and planning executive activities before and after attending the I.C.U ward showed that in a case study, the number of patients receiving services increased by an average of 17%.

2Uncertainty in the supply chain is a very important aspect that is caused by various reasons, including social and political developments, a lack of raw materials for production, etc. Considering the importance of society's health, the purpose of the current research is to evaluate the performance of drug distribution companies in terms of resilience. The present study is quantitative-qualitative research and is an applied type. The population and statistical sample include 15 experts in the field of medicine who were selected by purposeful sampling. Research data was collected using field methods, library studies, interviews, and questionnaires. Due to uncertainty in experts' opinions, a multi-criteria decision-making approach was used in type-1 fuzzy environment. State drug distribution companies in Bojnord city were ranked in terms of supply chain resilience indicators using the fuzzy WASPAS method. The weight and importance of the indicators were also obtained by the fuzzy Swara method. Then, to ensure the accuracy of the obtained results, the drug distribution companies were also ranked using the fuzzy SAW and fuzzy ARAS methods, and the results were compared. The results of the research showed that Daro Pakhsh, Hejrat, and Ferdows companies are ranked first to third in terms of supply chain resilience.

2Today, due to the growing expansion of the credit industry and the emergence of diverse loan portfolios, credit rating models are being developed more dynamically and accurately than in the past. So that even a few percent increase in customer accreditation accuracy has become particularly important. The purpose of this study is to present a ranking model in the space of intuitive fuzzy sets from a risk perspective. Data were collected from three sources: banking operating system, credit facility files in the archive and personal files of experts. The proposed model was extracted on 22 indicators in accordance with the criteria of the 5C validation model and the weight of each was determined by intuitive hierarchical analysis. The results of applying the proposed model showed that the credit rating of customers applying for bank facilities has improved significantly and the personal judgments of bank experts to calculate customers' credit score have decreased.

2Data envelopment analysis is a powerful method for evaluating the efficiency of homogeneous decision-making units with multiple inputs and outputs, which considers the internal structure of the units as a black box. In many real-world problems, decision-making units have a two-stage structure, and its inputs and outputs may be shared between stages. In practical problems, it is difficult to divide shared inputs and shared outputs and assign them to each of the stages. Therefore, to solve such problems, by developing two-stage data envelopment analysis models and using the non-compensatory property of the multiplication operator, a nonlinear model is introduced so that in addition to calculating the efficiency of the system and its stages, the optimal share (portion) of each stage in the using of the shared inputs and shared outputs is determined in order to obtain maximum efficiency. Finally, the data of 17 branches of the Central Bank in China are used to examine the application of the proposed model.