Reeves C R, Yamada T
School of Mathematical and Information Sciences, Coventry University, United Kingdom.
Evol Comput. 1998 Spring;6(1):45-60. doi: 10.1162/evco.1998.6.1.45.
In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly.
在之前的一篇论文中，开发了一种简单的遗传算法（GA），用于（近似地）求解n个作业、m台机器的排列流水车间排序问题（PFSP）的最小完工时间。该算法的性能与朴素邻域搜索技术和经过验证的模拟退火算法相当。然而，最近的结果表明禁忌搜索方法在解决PFSP方面具有优越性。在本文中，我们重新考虑针对此问题的遗传算法的实现，并表明通过考虑所用算子生成的景观特征，我们能够显著提高其性能。
