Abstract
Location and allocation problems in supply chain networks are considered as strategic decisions; because they both require investment and have long-term effects. On the other hand, the supply chain network is not protected against disruptions in the real world. In this paper, a branch and efficiency (B&E) algorithm is developed which integrates a multi-objective optimization model used for designing the supply chain network with an extended data envelopment analysis (EDEA) model. Through this integration, efficient solutions are obtained that lead to minimization of the costs. The objective functions of the optimization model include the operational costs, resilience costs and inequality in satisfying customer demand. Then, the efficiency of the solutions is measured using EDEA in terms of the costs, service level and traffic congestion. The solutions derived from EDEA are added to the multi-objective optimization model based on efficiency cuts. This iterative procedure continues until an efficient design is developed for the supply chain network. The proposed B&E algorithm is implemented on a real case using fuzzy goal programming to illustrate its applicability. The results show that the proposed algorithm has better performance in reducing the costs and measuring efficiency compared to the competing algorithms in the literature.
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Babaei, A., Khedmati, M. & Akbari Jokar, M.R. A new branch and efficiency algorithm for an optimal design of the supply chain network in view of resilience, inequity and traffic congestion. Ann Oper Res 321, 49–78 (2023). https://doi.org/10.1007/s10479-022-05080-w
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DOI: https://doi.org/10.1007/s10479-022-05080-w