Document Type : Research Paper
Authors
1 State Key Laboratory of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
2 State Key Laboratory of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract
Supply chain network design and resilient supplier selection play an important role in supply chain risk management to deal with various operational and disruption risks. In this paper, we develop a robust mathematical bi-objective, multi product model to consider resilient supplier and uncertainty in supply chain network design across multi period and multi products simultaneously, and this study offer optimal solutions for resilient supplier selection and order allocation. First we show a mixed-integer linear programming model with two objective functions, The first objective function maximizes the total profit, while the second maximizes the total supplier resilience score, where Fuzzy SECA have been used to obtain the five resiliency criteria weights and obtain the resilience scores for the objective function. we can rank the resilient suppliers using the fuzzy SECA method . we proposed an approach for coordination between production planning, supplier selection, and order allocation. The ε-constraint method was used to obtain optimum amounts of decision variables to maximize the profit for a real case study. Finally, a Pareto solution analysis has been done for the tradeoff between robustness and resilience.
the results show that how uncertainty parameters in the supply chain can affect the objective function. furthermore, this paper finds show that with supplier resilience score 4000, the first objective function of model present highest value, therefore in this point we can have resilient supplier with maximum profitability.
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