A Hybrid Genetic Algorithm for Job-Shop Scheduling Problem

被引：0
|
作者：
Wang Lihong [1 ]
Ten Haikun [2 ]
Yu Guanghua [3 ]
机构：
[1] Univ HeiHe, Sci & Informat Engn Dept, Res Direct Algorithm Res & Network Secur, CO-164300 Heihe, Heilongjiang Pr, Peoples R China
[2] Univ HeiHe, Sci & Informat Engn Dept, CO-164300 Heihe, Heilongjiang Pr, Peoples R China
[3] Univ HeiHe, Dept Comp Sci & Informat Engn, CO-164300 Heihe, Heilongjiang Pr, Peoples R China
来源：
2015 IEEE 28TH CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE) | 2015年
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A hybrid optimization algorithm is proposed for Job-Shop scheduling problem, which is based on the combination of adaptive genetic algorithm and improved ant algorithm. The algorithm gets the initial pheromone distribution using adaptive genetic algorithm at first, then runs improved ant algorithm. The algorithm utilizes the advantages of the two algorithms and overcomes their disadvantages. Experimental results show the algorithm excels genetic algorithm and ant algorithm in performance, and it is discovered that the bigger the problem is concerned, the better the algorithm performs.
引用
收藏
页码：271 / 274
页数：4
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