基于相似性遗传算法及其在JSP中的应用

提出一种基于个体相似性的改进算法, 当种群的多样性较好时,采用标准的交叉策略;当种群的多样性较差时,根据个体的相似性选择个体配对, 避免相同的个体配对交叉, 减少高度相似个体进行配对交叉的概率, 从而提高交叉操作的效率. 用该改进算法对基准作业车间调度问题（JSP）进行计算,仿真结果表明：该算法优于标准遗传算法.

A genetic algorithm based on similarity and its application on JSP

Standard genetic algorithms are often lost in local optimum because genetic operation is of low efficiency and unable to make out new chromosomes when the diversity of population is poor. This paper proposes an improved genetic algorithm based on the similarity of chromosomes. Standard crossover operation is used when the diversity of population is good; otherwise, chromosomes are matched based on their similarity, crossover between two very simi- lar chromosomes are avoided, and the probability of crossover between two very similar chromosomes is decreased. Thus, efficiency of crossover operation is improved. This algorithm was used to solve a benchmark of job shop sched- uling problems, the simulational result shows that this improved algorithm is effective.