南京理工大学学报（自然科学版）2018，Vol.42Issue(3)：345-351,7.DOI:10.14177/j.cnki.32-1397n.2018.42.03.013
基于改进免疫克隆选择算法的柔性作业车间调度
Flexible job-shop scheduling based on improved immune clone selection algorithm
摘要
Abstract
An improved immune clone selection algorithm is proposed to minimize the makespan for flexible job-shop scheduling problem( FJSP) . A flexible job-shop scheduling model is built. Several strategies are used to generate new antibodies in order to improve the quality of initial antibodies. An adaptive mutation operation is constructed. In light of the shortcomings of the standard immune algorithm,the diversity of population is kept by population decomposition in order to improve the ability of global search. A standard test case with 6 workpieces and 10 machines is simulated,the optimized results of makespan obtained by genetic algorithm, simulated annealing algorithm and immune algorithm are 47 s,48 s and 50 s respectively, and the result obtained by this improved algorithm is 45 s;the probability of getting the optimum solution of this improved algorithm is 75%.关键词
免疫克隆选择算法/柔性作业车间调度/自适应变异/种群分割Key words
immune clone selection algorithm/flexible job-shop scheduling/adaptive mutation/population decomposition分类
信息技术与安全科学引用本文复制引用
王雷,邹新..基于改进免疫克隆选择算法的柔性作业车间调度[J].南京理工大学学报（自然科学版）,2018,42(3):345-351,7.基金项目
安徽省自然科学基金(1708085ME129) （1708085ME129）
安徽省科技攻关项目(1604a0902183) （1604a0902183）
