Ant colony optimization based on pheromone trail centralization

被引：0

作者：

Zheng, Song ^{[1
]}

Zhang, Guanxing ^{[1
]}

Zhou, Zekui ^{[1
]}

机构：

[1] Zhejiang Univ, Dept Control Sci & Engn, Hangzhou 310027, Peoples R China

来源：

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年

关键词：

ant colony optimization; pheromone trail; traveling salesman problem; premature convergence;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Aiming at the disadvantage (premature convergence) of the Ant Colony Optimization (ACO), a mechanism called Pheromone Trail Centralization (PTC) is presented. The mechanism adjusts the pheromone trails proportionally and facilitates the exploration by increasing the probability of selecting solution components with low pheromone trail. It can avoid premature convergence of ACO and exploit more strongly solutions. The results show that ACO with PTC are superior to the existing ACO and the mechanism is useful to improve the performance of any versions of ACO by investigating the functioning of PTC in the Traveling Salesman Problem (TSP).

引用

页码：3349 / 3352

页数：4

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