A scenario-based robust possibilistic-flexible programming model for responsive supply chain network design with a performance-oriented solution methodology

Abstract

This study addresses an integrated multi-objective responsive supply chain network optimization problem under hybrid uncertain business environment and optimal scheme selection. In addition to economic performance, delivery time and delivery reliability, as responsiveness indicators, are introduced into the multi-objective mixed-integer linear programming model. To deal with hybrid uncertainties caused by various scenarios, parameters, and flexible constraints, a scenario-based robust possibilistic flexible programming approach is extended. Moreover, a performance-oriented solution method is developed to solve the multi-objective optimization problem. The method integrates meta-heuristic and entropy-weighted TOPSIS to perform performance evaluation together with iteration optimization. The set of non-dominant solutions obtained by evaluation guide the iteration process. The numerical case verifies the effectiveness and efficiency of the proposed model, uncertainty technical and solution method. Interestingly, Pareto optimal solution set and its sort obtained by evaluation provide the optimal network scheme with the best supply chain performance.