| 广义分配问题的一种小生境遗传蚁群优化算法 |
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| 引用本文： | 陈云飞,刘玉树,范洁,赵基海.广义分配问题的一种小生境遗传蚁群优化算法[J].北京理工大学学报,2005,25(6):490-494. |
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| 作者姓名： | 陈云飞 刘玉树 范洁 赵基海 |
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| 作者单位： | 北京理工大学,信息科学技术学院计算机科学工程系,北京,100081 |
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| 摘 要： | 提出一种小生境遗传算法与蚁群优化算法相结合的小生境遗传蚁群优化算法用于求解NP难的广义分配问题,以避免经典求解算法存在的易陷于局部最优的缺陷.以典型的广义分配问题——火力分配为例,对该算法进行实验,并将实验结果与其它算法进行分析比较.结果表明:新复合算法优化效率高,运行时间短,对其它的NP问题同样适用.
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| 关 键 词： | 小生境遗传算法 蚁群优化算法 广义分配问题 |
| 文章编号： | 1001-0645(2005)06-0490-05 |
| 修稿时间： | 2004年6月11日 |
A Niching Genetic and Ant Colony Optimization Algorithm for Generalized Assignment Problem |
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| CHEN Yun-fei,LIU Yu-shu,FAN Jie and ZHAO Ji-hai.A Niching Genetic and Ant Colony Optimization Algorithm for Generalized Assignment Problem[J].Journal of Beijing Institute of Technology(Natural Science Edition),2005,25(6):490-494. |
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| Authors: | CHEN Yun-fei LIU Yu-shu FAN Jie and ZHAO Ji-hai |
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| Institution: | Department of Computer Science and Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Computer Science and Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Computer Science and Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Computer Science and Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China |
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| Abstract: | A niching genetic and ant colony optimization (NGACO) algorithm is proposed for the NP hard generalized assignment problem. NGACO is based on the combination of niching genetic algorithm and ant colony optimization algorithm to avoid local optima which often reside in the results of classical methods. Moreover, an intensive study on how to use this algorithm in GAP is made. Some experiments were made on weapon-target assignment problem (a typical application of GAP). Experiments' results are compared with those obtained by using other classical optimization algorithms. The results demonstrated that NGACO has high performance and short runtime in solving weapon-target assignment problem, and is viable for other NP-hard problems. |
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| Keywords: | niching genetic algorithm ant colony optimization algorithm generalized assignment problem |
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