Ant Colony Optimization for Multi-Objective Optimization Problems

Ant Colony Optimization for Multi-Objective Optimization Problems
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DOI：
10.1109/ictai.2007.108
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发表时间：
2007-10
期刊：
19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)
影响因子：
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通讯作者：
I. Alaya;Christine Solnon;K. Ghédira
I. Alaya;Christine Solnon;K. Ghédira
中科院分区：
其他
文献类型：
--
作者：
I. Alaya;Christine Solnon;K. Ghédira

文献摘要

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本文提出了一种基于蚁群优化的遗传算法来求解多目标优化问题。该算法由蚁群数量和信息素路径数来参数化。我们比较不同的变种，这种算法的多目标背包问题。我们也比较所得到的结果与其他进化算法从文献中。
We propose in this paper a generic algorithm based on ant colony optimization to solve multi-objective optimization problems. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. We compare different variants of this algorithm on the multi-objective knapsack problem. We compare also the obtained results with other evolutionary algorithms from the literature.