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A Multiple Pheromone Table Based Ant Colony Optimization for Clustering
Joint Authors
Tsai, Chun-Wei
Chiang, Ming-Chao
Hu, Kai-Cheng
Yang, Chu-Sing
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-14
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Ant colony optimization (ACO) is an efficient heuristic algorithm for combinatorial optimization problems, such as clustering.
Because the search strategy of ACO is similar to those of other well-known heuristics, the probability of searching particular regions will be increased if better results are found and kept.
Although this kind of search strategy may find a better approximate solution, it also has a high probability of losing the potential search directions.
To prevent the ACO from losing too many potential search directions at the early iterations, a novel pheromone updating strategy is presented in this paper.
In addition to the “original” pheromone table used to keep track of the promising information, a second pheromone table is added to the proposed algorithm to keep track of the unpromising information so as to increase the probability of searching directions worse than the current solutions.
Several well-known clustering datasets are used to evaluate the performance of the proposed method in this paper.
The experimental results show that the proposed method can provide better results than ACO and other clustering algorithms in terms of quality.
American Psychological Association (APA)
Hu, Kai-Cheng& Tsai, Chun-Wei& Chiang, Ming-Chao& Yang, Chu-Sing. 2015. A Multiple Pheromone Table Based Ant Colony Optimization for Clustering. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073061
Modern Language Association (MLA)
Hu, Kai-Cheng…[et al.]. A Multiple Pheromone Table Based Ant Colony Optimization for Clustering. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073061
American Medical Association (AMA)
Hu, Kai-Cheng& Tsai, Chun-Wei& Chiang, Ming-Chao& Yang, Chu-Sing. A Multiple Pheromone Table Based Ant Colony Optimization for Clustering. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073061
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073061