A common interval guided ACO algorithm for permutation problems

Martin Clauss, Matthias Bernt, M. Middendorf
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引用次数: 2

Abstract

Ant Colony Optimization (ACO) has been successfully applied to many combinatorial optimization problems. In this work we propose a new solution construction scheme for ACO. This scheme uses the common intervals of the current iteration's best solutions to guide the ants during solution construction. Firstly, we compared the performance of ACO and the proposed algorithm Common Interval ACO (CIACO). Secondly, we conducted an in-depth study for the CIACO algorithm to investigate the influence of the common interval guidance. For both experiments a large parameter space was used. The results show, that common intervals can be used to improve the solution quality in comparison to the standard ACO algorithm.
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区间引导蚁群算法求解置换问题
蚁群算法已成功地应用于许多组合优化问题。本文提出了一种新的蚁群算法求解方案。该方案利用当前迭代的最佳解的公共间隔来指导蚂蚁在解构建过程中进行操作。首先,比较了蚁群算法与公共区间蚁群算法(CIACO)的性能。其次,我们对CIACO算法进行了深入的研究,探讨了公共区间制导的影响。两个实验都使用了较大的参数空间。结果表明,与标准蚁群算法相比,使用公共区间可以提高求解质量。
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