Hybrid genetic algorithm for job shop scheduling problem

doi:10.3778/j.issn.1002-8331.2008.29.019

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (29): 73-75.DOI: 10.3778/j.issn.1002-8331.2008.29.019

• 理论研究 • Previous Articles Next Articles

Hybrid genetic algorithm for job shop scheduling problem

LIU Sheng-hui¹,WANG Li-hong²

1.School of Software，Harbin University of Science and Technology，Harbin 150080，China
2.School of Computer，Harbin University of Science and Technology，Harbin 150080，China

Received:2007-11-26 Revised:2008-02-21 Online:2008-10-11 Published:2008-10-11
Contact: LIU Sheng-hui

求解车间作业调度问题的混合遗传算法

刘胜辉¹,王丽红²

1.哈尔滨理工大学软件学院，哈尔滨 150080
2.哈尔滨理工大学计算机学院，哈尔滨 150080

通讯作者: 刘胜辉

Abstract

Abstract: 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.

Key words: genetic algorithm, ant algorithm, job-shop, dynamic combination

摘要： 针对Job-Shop调度问题，将自适应遗传算法与改进的蚂蚁算法融合，提出了自适应遗传算法与蚂蚁算法混合的一种优化算法。首先利用自适应遗传算法产生初始信息素的分布，再运行改进的蚂蚁算法进行求解。该算法既发挥了自适应遗传算法和蚂蚁算法在寻优中的优势，又克服了各自的不足。实验结果表明，该算法在性能上明显优于遗传算法和蚂蚁算法，并且问题规模越大，优势越明显。

关键词: 遗传算法, 蚂蚁算法, 车间作业（job-shop）, 动态融合

LIU Sheng-hui¹,WANG Li-hong². Hybrid genetic algorithm for job shop scheduling problem[J]. Computer Engineering and Applications, 2008, 44(29): 73-75.

刘胜辉¹,王丽红². 求解车间作业调度问题的混合遗传算法[J]. 计算机工程与应用, 2008, 44(29): 73-75.

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Hybrid genetic algorithm for job shop scheduling problem

求解车间作业调度问题的混合遗传算法

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