计算机工程与应用Issue(11)：242-247,6.DOI:10.3778/j.issn.1002-8331.1310-0197
求解多目标PFSP的改进遗传算法
Improved genetic algorithm for multi-objective of PFSP
摘要
Abstract
An improved genetic algorithm is proposed for multi-objective of Permutation Flowshop Scheduling Problem (PFSP)to optimize the makespan and total flow time. In order to keep the diversity of the population, the initial popula-tion is generated by combining heuristic algorithm and random algorithm in the proposed algorithm. The procedure of evo-lution is completed with selection, crossover, mutation operation and update strategy. When population evolutionary stag-nated, the re-initialization mechanism is introduced to restore diversity. In addition, a variable neighborhood search algo-rithm is designed to accelerate population convergence and jump out of local optimum. Compared with several other opti-mization algorithms through experiment on the benchmarks, the results show that the proposed algorithm in both solution quality and stability is superior to other algorithms.关键词
多目标/置换流水车间调度/遗传算法/变邻域搜索Key words
multi-objective/permutation flowshop scheduling/genetic algorithm/variable neighborhood search分类
信息技术与安全科学引用本文复制引用
齐学梅,王宏涛,陈付龙,罗永龙..求解多目标PFSP的改进遗传算法[J].计算机工程与应用,2015,(11):242-247,6.基金项目
国家自然科学基金（No.61370050）；安徽省自然科学基金（No.1308085QF118）；安徽省高等学校质量工程项目（No.2012JYXM104）；安徽师范大学创新基金（No.2013CXJJ01）。 （）
