| 基于蚁群算法的多目标优化问题研究 |
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| 引用本文： | 孔翔宇,欧阳瑞. 基于蚁群算法的多目标优化问题研究[J]. 四川理工学院学报(自然科学版), 2010, 23(3): 344-347 |
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| 作者姓名： | 孔翔宇 欧阳瑞 |
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| 作者单位： | 1. 周口师范学院数学与信息科学系,河南,周口,466000;西安电子科技大学理学院,西安,710071
2. 周口师范学院数学与信息科学系,河南,周口,466000 |
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| 基金项目： | 周口师范学院青年基金 |
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| 摘 要： | 为保持所求得的多目标优化问题Pareto最优解的多样性,文章提出了一种新的蚁群算法。选择策略采用多信息素权重,信息素更新结合了局部信息素更新与全局信息素更新。其中,全局信息素更新采用了两个最好解。此外,通过在外部设置外部集来存储Pareto解,并将改进的算法应用在双目标TSP上。最后进行了仿真实验,结果表明新方法比NSGA-II和SPEA2更有效。
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| 关 键 词： | 多目标优化 蚁群算法 双目标TSP |
Multi-objective Optimization Based on Ant Colony Algorithm |
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| KONG Xiang-yu,OUYANG Rui. Multi-objective Optimization Based on Ant Colony Algorithm[J]. Journal of Sichuan University of Science & Engineering(Natural Science Editton), 2010, 23(3): 344-347 |
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| Authors: | KONG Xiang-yu OUYANG Rui |
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| Abstract: | In order to preserve the diversity of Pareto optimal solutions in multi-objective optimization problems,A new ant colony algorithm is proposed.In the proposed algorithm,the selection strategy is multi-pheromone-weighted,and pheromone update uses the combination of the local and global pheromone update.Especially,the global pheromone update adopts the best solution and the second-best solution.In addition,an external set is set up outside to store the Pareto solution,and the improved algorithm is used to solve the bi-criterion TSP.The experiment show that the new algorithm is more efficient than SPEA2 and NSGA-II. |
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| Keywords: | multiple objective optimization ant colony optimization bi-criteria TSP |
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