【摘要】 搜索空间适应性的遗传算法(GSA)具有这样的能力,即使在不通过修改遗传算法的某些参数(例如交叉率和变异率)的情况下,就可适应解空间的结构、并调节全局搜索和局部搜索的相互平衡。但是这种遗传算法(GSA)需有对个体特征继承率控制能力的交叉操作。文章阐述了一种改进的搜索空间适应性的遗传算法(mGSA)用于解决车间作业调度问题(JSP);这种方法不同于GSA不需要带特征继承率调节能力的交叉操作。最后通过两个benchmark问题的数字实验,展示了这种方法的的有效性;并通过与现存的遗传算法相比较,展示了这种方法有更好的结果。更多还原

【Abstract】 The genetic algorihm with search area adaptation(GSA)can adapting to the structure of solution space and controlling the tradeoff balance between global and local searches even if we do not adjust the parameters of the genetic algorithm(GA)(such as crossover and mutation rates).But GSA needs the crossover operator that can control characteristic inheritance ratio.In this paper,we propose the modified genetic algorithm with search area adaptation(mGSA) for solving the Job-shop scheduling problem(JSP).Unlike GSA,the method does not need such a crossover operator.We conduct numerical experiments of bechmark problems,the result showes that this method has better performance.更多还原