Supplier selection and order allocation model with disruption and environmental risks in centralized supply chain

作     者：Rezaei, Aida Aghsami, Amir Rabbani, Masoud 

作者机构：Univ Tehran Coll Engn Sch Ind & Syst Engn Tehran Iran KN Toosi Univ Technol Sch Ind Engn Tehran Iran 

出 版 物：《INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT》 (国际系统保证工程与管理杂志)

年 卷 期：2021年第12卷第6期

页      面：1036-1072页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 1202[管理学-工商管理] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0837[工学-安全科学与工程] 0823[工学-交通运输工程] 

主　　题：Resilient supply chain Supplier selection and order allocation Disruption risks Nonlinear mixed-integer programming Failure mode and effects analysis Grasshopper optimization algorithm 

摘      要：Supply chain managers have realized that competition between supply chains has replaced competition between companies. In addition, with increasing disruptions and uncertainty in planning, companies need to be able to make informed decisions at risk. Coordination in the resilient supply chain and appropriate selection of suppliers play a key role in risky situations. In previous research, mainly the impact of resilience strategies in the decentralized supply chain has been investigated and ignored the reliability of suppliers in the decision-making process. Therefore, we provide an effective framework for selecting reliable suppliers and order allocation, which increases the supply chain s benefits by considering the risk reduction strategies and coordination between the buyer and the supplier. Thus, we optimized the problem of supplier selection and order allocation in a centralized supply chain using mixed-integer nonlinear programming models and risk reduction strategies. These strategies are protected suppliers, back-up suppliers, reserving additional capacity, emergency stock, and geographical separation. Also, by considering the failure mode and effects analysis technique and the risk priority number constraint, suppliers reliability has been considered. A numerical example is solved with the exact method. In addition, the application of the proposed models in a case study has been investigated by the Grasshopper optimization algorithm. Based on the sensitivity analysis results, we found that the simultaneous use of risk reduction strategies in the models significantly reduces supply chain costs and increases its benefits. Also, considering the reliability constraints causes supply chain managers to choose suppliers with more desirable reliability.