A Multi-Population Genetic Algorithm for Job Shop Scheduling Problem

CAI Liang-wei; ZHANG Ji-hong; LI Xia

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A Multi-Population Genetic Algorithm for Job Shop Scheduling Problem

更新时间：2025-07-16

- A Multi-Population Genetic Algorithm for Job Shop Scheduling Problem
- Acta Electronica Sinica Vol. 33, Issue 6, Pages: 991-994(2005)
- 作者机构：
  
  深圳大学电子工程系,广东,深圳,518060
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP273
- Published：2005
- 稿件说明：
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CAI Liang-wei, ZHANG Ji-hong, LI Xia. A Multi-Population Genetic Algorithm for Job Shop Scheduling Problem[J]. Acta Electronica Sinica, 2005, 33(6): 991-994.
DOI：

CAI Liang-wei, ZHANG Ji-hong, LI Xia. A Multi-Population Genetic Algorithm for Job Shop Scheduling Problem[J]. Acta Electronica Sinica, 2005, 33(6): 991-994. DOI：

摘要

针对最小化完工时间的作业车间调度问题提出一个多种群遗传算法

该算法基于工艺约束定义个体的编码方式

基于工件操作构造遗传算子

保证了所有个体的可行性;多种群算法通过各个种群之间的相互竞争和良种共享

提高了资源的利用效率

有效地克服个体早熟

改善了算法的收敛性能.典型测试算例表明该算法是非常有效的.

Abstract

A multi-population genetic algorithm is presented for Job Shop scheduling problem targeting to minimize the makespan.The coding scheme of chromosomes is defined based on the process constraints

genetic operators are defined according to job operations

so all chromosomes are feasible.By the competition and sharing mechanism among populations

the computing resource is utilized more efficiently

and prematurity is overcome effectively.These improve the convergence of the multi-population genetic algorithm.Experiments on Job Shop Benchmarks show that this algorithm has good performance.

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