Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (22): 41-43.

• 学术探讨 • Previous Articles     Next Articles

Improved genetic algorithm for permutation Flow-shop scheduling problem

YI Hua-wei1,ZHANG Qiu-yu2   

  1. 1.School of Computer Science and Engineering,Liaoning Institute of Technology,Jinzhou,Liaoning 121001,China
    2.School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-08-01 Published:2007-08-01
  • Contact: YI Hua-wei

求解置换Flow-shop调度问题的改进遗传算法

伊华伟1,张秋余2   

  1. 1.辽宁工学院 计算机科学与工程学院,辽宁 锦州 121001
    2.兰州理工大学 计算机与通信学院,兰州 730050
  • 通讯作者: 伊华伟

Abstract: An improved genetic algorithm for permutation Flow-shop scheduling problem is proposed.The algorithm adopts multi-individual-crossover way,takes the threshold value in the process of crossover and mutation,thus expands the search zone of solution space and keeps the variety of the population in the course of optimizing,increases the probability of obtaining optimum solution.Through testing a series of typical Benchmark problems,the results validate the effectiveness of the proposed algorithm.

Key words: genetic algorithm, permutation Flow-shop scheduling problem, multi-individual-crossover, threshold value, population, Benchmark problem

摘要: 提出一种求解置换Flow-shop调度问题的改进遗传算法。该算法采用多个体交叉方式,对交叉过程和变异过程分别进行阈值设置,实现了在优化过程中扩大解空间的搜索范围和保持种群的多样性,从而增大了获得最优解的几率。最后对一系列典型的Benchmark问题进行仿真测试,实验结果证实了该改进遗传算法的有效性。

关键词: 遗传算法, 置换Flow-shop调度问题, 多个体交叉, 阈值, 种群, Benchmark问题