Dynamic Performance Optimization of the Supply Chain with Nonlinear Constraints

Abstract

The dynamic performance of supply chain system presents a characteristic of complexity in its stable region. It is important to coordinate and optimize the multi-dynamic performance of the supply chain system under the premise of ensuring its stability. Based on APIOBPCS, an index system of multi-dynamic performance is established. Thus, the system can achieve Pareto optimal via the Non-dominated Sorting Genetic Algorithm. According to the optimization and comparison of the three different nonlinear models on the basis of APIOBPCS, this paper summarizes the properties of Pareto frontier and solution sets. Moreover, the major influence of parameters on indexes is provided, and its inherent principle is explored through simulation experiments. Finally, managerial suggestions are proposed to improve the efficiency of supply chain on the basis of the research achievements.