计算机集成制造系统 ›› 2015, Vol. 21 ›› Issue (第4期): 1032-1039.DOI: 10.13196/j.cims.2015.04.018

• 产品创新开发技术 • 上一篇    下一篇

求解混合流水车间调度问题的变量相关EDA算法

刘昶1,李冬1,2,彭慧1,史海波1   

  1. 1.中国科学院沈阳自动化研究所
    2.中国科学院大学
  • 出版日期:2015-04-30 发布日期:2015-04-30
  • 基金资助:
    国家科技重大专项资助项目(2011ZX02601-005)。

EDA algorithm with correlated variables for solving hybrid flow-shop scheduling problem

  • Online:2015-04-30 Published:2015-04-30
  • Supported by:
    Project supported by the National Science and Technology Major Project,China(No.2011ZX02601-005).

摘要: 针对混合流水车间调度问题和分布估计算法的特点,提出将变量按工序分组,通过组内概率约束、组间概率耦合的方式建立混合流水车间调度问题变量间概率关系的新方法。对分布估计算法中的紧致遗传算法的种群产生和概率更新机制进行了改进,以解决流水车间调度问题等复杂问题。通过仿真实验、与其他算法比较以及在大规模生产实际问题中的应用,验证了该算法的有效性和鲁棒性。

关键词: 分布估计算法, 紧致遗传算法, 混合流水车间, 概率模型

Abstract: According to the characteristic of Hybrid Flow-shop Scheduling Problem (HFSP) and Estimation of Distribution Algorithm (EDA),a new method of building probabilistic relationships between HFSP variables was proposed.In this new method,the variable was grouped by process,and the variable probabilistic relationship in a high level was built through the probabilistic constraints in the same group and the probabilistic coupling in different groups.The mechanism of population generation and probability updating was improved in the standard compact Genetic Algorithm(cGA)which accelerated the convergence rate of algorithm.The effectiveness and robustness of the algorithm was proved by simulation and the comparison with other algorithms and the verification of large-scale practical problem.

Key words: estimation of distribution algorithm, compact genetic algorithm, hybrid flow-shop, probability model

中图分类号: