引用本文:唐立新，刘继印.改进遗传算法及其在带有目标是最小平均总流程时间的流水调度排序中的应用[J].控制理论与应用,1999,16(3):442~444.[点击复制]
Tang Lixin，Liu Jiyin.A Modified Genetic Algorithm and Its Application to the FlowshopSequencing Problem with objective of Minimizing Mean Total Flowtime[J].Control Theory and Technology,1999,16(3):442~444.[点击复制]
改进遗传算法及其在带有目标是最小平均总流程时间的流水调度排序中的应用
A Modified Genetic Algorithm and Its Application to the FlowshopSequencing Problem with objective of Minimizing Mean Total Flowtime
摘要点击 787  全文点击 478  投稿时间：1998-06-08  修订日期：1998-11-23
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DOI编号  
  1999,16(3):442-444
中文关键词  改进遗传算法  流水调度问题  平均总流程时间
英文关键词  modified genetic algorithm  flowshop scheduling  mean total flowtime
基金项目  
作者单位
唐立新，刘继印  
中文摘要
      提出了一个改进遗传算法的结构，并且应用于带有目标是最小平均总流程时间的流水调度排序中。为了改进一般遗传算法的程序，两个新的操作被引进到这个操作中，这两个操作为：1）过滤操作：过滤掉在每一代中的最坏的个体，用前一代中的最好的个体替代它；2）培育操作：当在一定代数内算法不改进时，选择一个培育操作作用于培育最有希望的个体。通过大量的随机产生的问题的例子的计算机实验显示出，提出的算法的性能明显好于一般遗传算法，并且和此问题的最好的专门意义的启发式算法相匹配。新的MGA框架很容易扩展到其它最优化当中，只是实施的详细的步骤有所不同。
英文摘要
      A modified genetic algorithm ()MGA) framework was developed and applied to the flowshop sequencing problems with objective of minimizing mean total flowtime. To improve the general genetic algorithm routine, two operations were introduced into the framework. Firstly, the worst points were filtered off in each generation and replaced with the best individuals found in previous generations; Secondly, the most promising individual was selectively cultivating if a certain number of recent generation have not been improved yet. Under conditions of flowshop machine, the initial population generation and crossover function can also be improved when the MGA framework is implemented. Computational experiments with random samples show that the MGA is superior to general genetic algorithm in performance and comparable to special-purpose heuristic algorithms. The MGA framework can also be easily extended to other optimizations even though it will be implemented differently in detail.