Multi-objective biogeography-based optimization for supply chain network design under uncertainty

摘要: We develop a new two-stage optimization method for MO-SCND under uncertainty.The proposed model includes uncertain transportation costs and customer demands.An approximation is adapted to approximate original model.A MO-BBO algorithm designed solve the model.Computational results demonstrate effectiveness of algorithm. This paper proposes multi-objective supply chain network design (MO-SCND) problem with demands. On basis risk-neutral risk-averse criteria, we two objectives our SCND problem. introduce solution concepts problem, use them define value fuzzy (MOVFS). The MOVFS measures importance uncertainties included in model, helps us understand necessity solving model. When demands have joined continuous possibility distributions, employ an approach (AA) compute values objective functions. Using AA, becomes approximating mixed-integer programming To hard improved biogeography-based (MO-BBO) integrated LINGO software. also compare genetic (MO-GA). Finally, realistic dairy company example provided that achieves better performance than MO-GA terms quality.