| 求解车间作业调度问题的混合遗传算法 |
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| 引用本文： | 刘胜辉,王丽红.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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| 作者姓名： | 刘胜辉 王丽红 |
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| 作者单位： | 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 |
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| 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。
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| 关 键 词： | 遗传算法 蚂蚁算法 车间作业(job-shop) 动态融合 |
| 收稿时间： | 2007-11-26 |
| 修稿时间： | 2008-2-21
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Hybrid genetic algorithm for job shop scheduling problem |
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| LIU Sheng-hui,WANG Li-hong.Hybrid genetic algorithm for job shop scheduling problem[J].Computer Engineering and Applications,2008,44(29):73-75. |
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| Authors: | LIU Sheng-hui WANG Li-hong |
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| Affiliation: | 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 |
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| 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. |
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| Keywords: | genetic algorithm ant algorithm job-shop dynamic combination |
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