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一种求解job shop问题的混合多目标遗传算法
引用本文:师瑞峰 周泓 上官春霞. 一种求解job shop问题的混合多目标遗传算法[J]. 计算机工程与应用, 2005, 41(30): 1-5,133
作者姓名:师瑞峰 周泓 上官春霞
作者单位:北京航空航天大学经济管理学院,北京100083
基金项目:国家自然科学基金资助(编号:70371005)
摘    要:提出一种基于操作编码、采用递进策略与非劣解局部搜索相结合的混合多目标遗传算法。通过将递进进化模式和非劣解局部搜索策略引入到算法结构,改善了算法对解空间的遍历性与算法的收敛性。采用改进算法对典型的jobshop算例进行三目标优化,所得结果验证了算法的有效性。

关 键 词:递进进化  多目标遗传算法  job  shop  局部搜索
文章编号:1002-8331-(2005)30-0001-05
收稿时间:2005-08-01
修稿时间:2005-08-01

A Hybrid Multi-objective Genetic Algorithm and Its Applications to Job Shop Problems
Shi Ruifeng, Zhou Hong, Shangguan Chunxia. A Hybrid Multi-objective Genetic Algorithm and Its Applications to Job Shop Problems[J]. Computer Engineering and Applications, 2005, 41(30): 1-5,133
Authors:Shi Ruifeng   Zhou Hong   Shangguan Chunxia
Affiliation:School of Economics and Management,Beihang University,Beijing 100083
Abstract:Job shop problem is one of the best-known NP-Hard combinatorial optimization problems.Many researchers have devoted to find an effective algorithm to solve multi-objective job shop problems.A hybrid multi-objective genetic algorithm is proposed in this paper,which is based on operation-coded with an integration of escalating evolution and Pareto local search strategy.The new algorithm has been applied to some typical three-objective job shop problems,its outstanding performance is illustrated with the optimization results.
Keywords:escalating evolution  multi-objective genetic algorithm  job shop  local search
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