Research on Job-shop Scheduling Problem Based on Improved Particle Swarm Optimization

QIAO Pei-li; MA Li-li; ZHENG Lin

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Research on Job-shop Scheduling Problem Based on Improved Particle Swarm Optimization

更新时间：2026-07-10

- Research on Job-shop Scheduling Problem Based on Improved Particle Swarm Optimization
- Vol. 16, Issue 2, Pages: 35-39(2011)
- 作者机构：
  
  哈尔滨理工大学计算机科学与技术学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TH186
- Published：2011
- 稿件说明：
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QIAO Pei-li, MA Li-li, ZHENG Lin. Research on Job-shop Scheduling Problem Based on Improved Particle Swarm Optimization[J]. 2011, 16(2): 35-39.
DOI：

QIAO Pei-li, MA Li-li, ZHENG Lin. Research on Job-shop Scheduling Problem Based on Improved Particle Swarm Optimization[J]. 2011, 16(2): 35-39. DOI：

摘要

针对现行的遗传算法存在过早收敛和进化速度过慢的局限

以及标准粒子群算法收敛精确度不高、易陷入局部极值点的缺点

通过分析原有算法的优化机理

提出一种惯性权重随粒子的进化代数增加而非线性减小的改进型粒子群算法

并将此算法应用于车间作业调度问题中.大量仿真实验结果表明

该算法在求解车间作业调度问题上具有可行性和有效性.

Abstract

Because the current genetic algorithms has the limitation of a premature convergence and the slow-evolutionary

and the standard particle swarm optimization has the shortcomings of low convergence precision

through analyzing the mechanism of the original optimization algorithm

this article proposes an improved particle swarm optimization in which inertia weight non-linear decreases with the increase of iterative generation

and applies this algorithm in job-shop scheduling problem.A large number of simulation...

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