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

机译:基于改进遗传算法的汽车零部件车间生产调度问题的求解

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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.
机译:目前,许多生产公司都存在生产线的非加工时间长,每个工位调度困难,生产资源利用率低等问题。本文以汽车零部件售后公司的生产数据为例,提出了汽车零部件柔性件车间的生产资源调度问题,并运用和改进了遗传算法来解决。比较了两种基于二维矩阵的编码方法和基于机器过程的分段编码。增加了进化逆向运算,以提高遗传算法的局部搜索能力,从而使算法的每一代都可以从父代遗传更多的基因。本文利用MATLAB对数据进行处理,并对调度结果进行仿真,证明了该算法的可行性和有效性。

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