ID 61414
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Author
Tamura, Yoshiki Graduate School of Natural Science and Technology, Okayama University
Sakiyama, Tomoko Department of Information Systems Science, Faculty of Science and Engineering, Soka University
Arizono, Ikuo Graduate School of Natural Science and Technology, Okayama University ORCID Kaken ID researchmap
Abstract
Ant colony optimization (ACO), which is one of the metaheuristics imitating real ant foraging behavior, is an effective method to ?nd a solution for the traveling salesman problem (TSP). The rank-based ant system (AS(rank)) has been proposed as a developed version of the fundamental model AS of ACO. In the AS(rank), since only ant agents that have found one of some excellent solutions are let to regulate the pheromone, the pheromone concentrates on a specific route. As a result, although the AS(rank) can find a relatively good solution in a short time, it has the disadvantage of being prone falling into a local solution because the pheromone concentrates on a specific route. This problem seems to come from the loss of diversity in route selection according to the rapid accumulation of pheromones to the specific routes. Some ACO models, not just the AS(rank), also suffer from this problem of loss of diversity in route selection. It can be considered that the diversity of solutions as well as the selection of solutions is an important factor in the solution system by swarm intelligence such as ACO. In this paper, to solve this problem, we introduce the ant system using individual memories (ASIM) aiming to improve the ability to solve TSP while maintaining the diversity of the behavior of each ant. We apply the existing ACO algorithms and ASIM to some TSP benchmarks and compare the ability to solve TSP.
Published Date
2021-01-08
Publication Title
Complexity
Volume
volume2021
Publisher
Wiley
Start Page
6610670
ISSN
1076-2787
NCID
AA11038146
Content Type
Journal Article
language
英語
OAI-PMH Set
岡山大学
Copyright Holders
© 2021 Yoshiki Tamura et al.
File Version
publisher
DOI
Web of Science KeyUT
Related Url
isVersionOf https://doi.org/10.1155/2021/6610670
License
https://creativecommons.org/licenses/by/4.0/
Funder Name
Japan Society for the Promotion of Science
助成番号
18K04611