Fostering supply chain resilience for omni-channel retailers: A two-phase approach for supplier selection and demand allocation under disruption risks

This study aims to optimize supplier selection and demand allocation decisions for omni-channel (OC) retailers to achieve supply chain resilience under the potential disruption risks. A two-phase approach with resilience factors that covers three main sourcing issues (i.e., supplier evaluation, supplier selection, and demand allocation) is proposed to support the decision-making. In the first phase, we construct a five-dimensional evaluation framework for OC retailers to identify supplier preferences and a hybrid model that combines the best-worst method to determine the weights of the evaluation criteria and evidential reasoning to evaluate potential suppliers. In the second phase, the preferences obtained from multiple suppliers are integrated into a multi-objective mixed integer linear programming model aiming to minimize expected cost and maximize total purchasing value and geographical segregation based on three key resilience strategies of multiple sourcing, geographic diversification, and local sourcing. The efficiency of the aforementioned resilience strategies as well as the solvability of the proposed model are then validated numerically using a real-world case study and various MOEAs. The outcomes could be used as a decision-making tool to assist OC retailers in the performance assessment and optimal demand allocation among the alternative suppliers by considering costs, purchase value, and resilience simultaneously.