计算机应用研究2017，Vol.34Issue(9)：2594-2598,5.DOI:10.3969/j.issn.1001-3695.2017.09.007
多群体混合进化算法求解IPPS问题
Multi-group hybrid evolutionary algorithm for solving IPPS problem
摘要
Abstract
For integrated process planning and scheduling (IPPS) problems solving complexity,in order to improve computational efficiency,this paper designed a multi-group hybrid evolutionary algorithm including explore population,optimum population and optimal population.The algorithm used hybrid genetic algorithm and the differential evolution algorithm based clustering mechanism to update processing chains and process order chains of explore population respectively,kept the diversity and difference of feasible solutions.Then it used the clone and field searching algorithm to complete clone and search of feasible solutions in the optimum populations,improved the quality of populations further.Finally,through the example calculation and comparison,the calculation results indicate that thealgorithm can improve searching efficiency and solving quality,and has good stability,which shows the feasibility and superiority of the algorithm to solve the IPPS problem.关键词
工艺规划与调度/聚类/差分进化算法/克隆Key words
process planning and scheduling/clustering/differential evolution algorithm/clone分类
信息技术与安全科学引用本文复制引用
杜轩,潘志成,张屹,陆瞳瞳..多群体混合进化算法求解IPPS问题[J].计算机应用研究,2017,34(9):2594-2598,5.基金项目
国家自然科学基金资助项目(51275274,71501110) （51275274,71501110）
湖北省自然科学基金资助项目(2014CFC1141) （2014CFC1141）
