Solving multi-objective supplier selection and quota allocation problem under disruption using a scenario-based approach

Nowadays, experts believe there are abundant sources of risks in a supply chain. An important group of risks against a supply chain is the disruption risks group, which disturbs the flow of material in the chain and may lead to inefficiency in providing the final product in the supply chain. The aim of this article is to investigate the control of costs of disruption in a supply chain by considering the possibility of disruption. In fact, this research focuses on determining the best combination of suppliers and quota allocation with regards to disruption in suppliers. The proposed multi-objective mathematical model in this paper is a mixed-integer programming (MIP) model with objective functions to minimize transaction costs of suppliers, expected costs of purchasing goods, expected percentages of delayed products, expected returned products, and to maximize expected evaluation scores of the selected suppliers. Due to the uncertainty of demand and supplier disruption in the real world, their values are also considered uncertain; the proposed multi-objective model is studied by using a scenario-based stochastic programming (SP) method. In this method, all possible predictions for demand and disruption values are simultaneously included in the model; objective function results have more optimal value than a separate solution of the model for each predicted value.