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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems Vol.21 No.3
- 발행연도
- 2022.9
- 수록면
- 475 - 491 (17page)
- DOI
- 10.7232/iems.2022.21.3.475
이용수
초록· 키워드
오류제보하기
Today, reverse logistics networks are increasingly expanding in various industries due to considering parameters such as environmental conditions, customer awareness, economic savings, social responsibilities, and gaining points such as customer loyalty. In the design of the reverse logistics network, the options of taking parts, repair, recycling, reproduction, and disposal can be considered. In this research, an integrated forward/reverse logistics network is modeled and an attempt is made to provide a general model and by adding the recycling option to the previous models, to a more general optimization model that includes more recovery options. It is achieved and the network should be optimized in the forward and reverse mode at the same time, taking into account the production of various products, first with the assumption of known demand and return, and then by fuzzing the parameters with uncertainty, as well as the limited capacities of the network centers. To defuzzification of this model, a method based on alpha cut is used for cost coefficients of decision variables and the center of mass method for demand and fuzzy return in the objective function. In fuzzy limits, a method based on the comparison of fuzzy numbers is used. In order to show the application of the Mixed Integer Linear Programming results, several examples have been simulated and coded in GAMS software to obtain accurate answers. In order to solve the model in large dimensions of the problem, a multi-objective genetic algorithm has been developed and coded by MATLAB software. The results of solving the examples in both cases, the exact and near-optimal solutions obtained from the genetic algorithm, have been compared and at the end, the sensitivity analysis of the network has been done. The obtained results show that considering imprecise parameters in a fuzzy manner, firstly, a more realistic model is obtained. Secondly, in examining the answer, due to their connection, the decision maker has unlimited options for the correct decision according to the existing conditions.
목차
ABSTRACT
1. INTRODUCTION
2. LITERATURE REVIEW
3. METHODOLOGY
4. THE PROPOSED MODEL
3. FULFILLING CUSTOMER DEMAND IN THE MOST POSSIBLE WAY
5. CONCLUSION
REFERENCES
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