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A novel Physarum-Based ant colony system for solving the real-world traveling salesman problem
The solutions to Traveling Salesman Problem can be widely applied in many real-world problems. Ant colony optimization algorithms can provide an approximate solution to a Traveling Salesman Problem. However, most ant colony optimization algorithms suffer premature convergence and low convergence rate. With these observations in mind, a novel ant colony system is proposed, which employs the unique feature of critical tubes reserved in the Physaurm-inspired mathematical model. A series of experiments are conducted, which are consolidated by two realworld Traveling Salesman Problems. The experimental results show that the proposed new ant colony system outperforms classical ant colony system, genetic algorithm, and particle swarm optimization algorithm in efficiency and robustness.
History
Title of book
Advances in Swarm IntelligenceVolume
8794Series
Lecture Notes in Computer ScienceChapter number
20Pagination
173 - 180Publisher
Springer VerlagPlace of publication
SwitzerlandPublisher DOI
ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319118574Language
engPublication classification
B Book chapter; B1 Book chapterCopyright notice
2014, SpringerExtent
56Editor/Contributor(s)
Y Tan, Y Shi, C CoelloUsage metrics
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