Multi-objective spare parts supply network optimization : model formulation and optimal decision-making

In order to solve the problem of strategic positioning and tactical decision-making of supply chain network design, the three-level spare parts supply network with different importance level of customers is studied. The multiobjective optimization model is established with the total transport time and demand satisfaction rate of the supply chain network as the fitness function and the total cost and flow as the constraints. The MOPSO algorithm is used to solve the problem and obtain a set of non-dominant solutions. For comprehensively measuring the performance of these solutions, suitable evaluation metrics are selected, and the cross-efficiency Data Envelopment Analysis (DEA) model has been used to evaluate and sort the efficiency of the obtained schemes, so as to select the optimal supply scheme, which can help the decision-maker to make scientific decisions.