Solving Production Scheduling Problem of Automotive Parts Workshop Based on Improved Genetic Algorithm

Abstract

At present, many production companies have problems such as long non-processing time of production lines, difficulty in scheduling of each station, and low utilization of production resources. This article takes the production data of auto parts after-sales company as an example, puts forward the production resource scheduling problem of the flexible parts workshop of auto parts, and uses and improves the genetic algorithm to solve the problem. The two coding methods two-dimensional matrix-based machine coding and the machine process segmented coding are compared. The evolution reversal operation was added to improve the local search ability of the genetic algorithm, so that each generation of the algorithm can inherit more genes from the parent. This paper uses MATLAB to process the data and simulate the scheduling results, which proves the feasibility and effectiveness of the algorithm.