Research on Assembly Scheduling of Complex Electromechanical Products Based on Improved Particle Swarm Optimization

Abstract

The assembly shop production scheduling of complex electromechanical products is a typical discrete variable NP-hard problem. In order to solve the assembly job scheduling problem of a large transformer assembly shop, an improved particle swarm algorithm is used to solve the optimal assembly task scheduling result. In order to minimize the maximum completion time, the traditional particle swarm optimization (PSO) algorithm was improved according to the characteristics of large transformer assembly process. First, the two-stage coding method of process and assembly team is adopted. Then, in order to improve the quality of the initial solution, the initialization method that minimizes the completion time is selected, and the adaptive inertia weight optimization speed update formula is adopted. Finally, the simulation study is carried out with relevant example data. Compared with the traditional PSO, the maximum completion time and convergence speed are significantly improved, which verifies the effectiveness of the improved PSO, and obtains the production scheduling Gantt chart of the workshop.