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Research on an improved ACO algorithm based on multi-strategy for solving TSP

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成果类型:
期刊论文
作者:
Li, Mengxing;Wan, Zhuo*
通讯作者:
Wan, Zhuo
作者机构:
[Wan, Zhuo; Li, Mengxing] School of Communication and Electronic Engineering, Hunan City University, Yiyang, Hunan, 41300, China
语种:
英文
期刊:
International Journal of Hybrid Information Technology
ISSN:
1738-9968
年:
2016
卷:
9
期:
9
页码:
323-334
机构署名:
本校为第一机构
院系归属:
信息与电子工程学院
摘要:
Ant colony optimization (ACO) algorithm is a metaheuristic inspired by the behavior of real ants in their search for the shortest path to food sources. The ACO algorithm takes on these characteristics of robust, positive feedback distributed computing, easy fusing with other algorithms. But the basic ACO algorithm has some deficiencies of premature and stagnation phenomenon in the evolution process, and is easily trapped into local optimal solution. And it is difficult to explore other solutions in the neighbor space. So a improved ACO(DPSEMACO) algorithm based on dual population strategy, bi-...

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