Resilient supplier selection and order allocation under uncertainty

Increasing the number of disasters around the world decreases the performance of supply chain. The decision makers should design resilient supply chain networks that can encounter disruptions. This paper develops an integrated resilient model for supplier selection and order allocation. Resilience measures including quality, delivery, technology, continuity, and environmental competences were explored for determining the Resilience Weight (RW) of suppliers. Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) methods were applied to finding the overall performance of each supplier. Then, the developed mathematical model maximized the overall performance of suppliers while minimizing total cost of network. The proposed mathematical model helps the decision makers to select supplier and allocate the optimum order quantities by considering shortage. Since the disruptive incidents are inevitable events in real-world problems, the impact of disruptions on suppliers, manufacturers, and retailers has been considered in the proposed model. Inherent uncertainties of parameters were taken into account to increase the compatibility of the approach with realistic environments. To tackle the uncertainty and multi-objectiveness of the proposed model, interval method and TH aggregation function were adapted. The proposed model was validated through its application to a real case study of a furniture company. Results demonstrated usefulness and applicability of the proposed model. (C) 2020 Sharif University of Technology. All rights reserved.