An improved genetic algorithm for Job-shop scheduling problem

摘要：

Because selection, crossover, mutation were all random, they might destroy the present individual which had the best fitness, then impacted run efficiency and converge. So used the strategy reserve the best individual, then the average fitness of chromosomes was improved, and the loss of the best solution was prevented. At the same time introduced the probability of crossover and mutation based on fitness, then it enhanced the genetic algorithms evolution ability, and the speed of the evolution was increased. And we find it is effective when solve the Job-shop scheduling problem.

关键词： production scheduling Job-shop scheduling genetic algorithm The strategy reserve the best individual

作者: Lou Xiao-fang Zou Feng-xing Gao Zheng Zeng Ling-li Ou Wei

作者单位: Department of Automatic Control, College of Mechatronics and Automation, National University of Defe Department of Educational Research,Border Cadre Training Center,Xi’an Military Academy, Urumchi, 830

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 2595-2598

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）