A MS-PSO Algorithm for Production Decisions of Electronic Products

In order to effectively solve the problem of multi-stage decision optimization, the Multi-Stage Particle Swarm Optimization (MS-PSO) algorithm is proposed in this paper, which aims to improve the overall efficiency and economic benefits in the manufacturing process of electronic products by optimizing various factors in production decisions. The composite fitness function is considered in the design of particle fitness function, combining local and global objectives, ensuring that both the local optimal solution and the global optimum solution can be find for the algorithm, without losing in the optimization process. Experimental results show that MS-PSO not only performs well in standard environment, but also still maintains high accuracy and stability in complex environments with high noise and strong nonlinearity. MS-PSO can optimize the testing and disassembly decisions, maximize profits, meanwhile effectively reduce redundant steps and costs in production.