A new minimum pheromone threshold strategy (MPTS) for max-min ant system
In recent years, various metaheuristic approaches have been created to solve quadratic assignment problems (QAPs). Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. Although it has solved some QAPs successfully, it still contains some w...
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2009
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my.utm.87502022-04-29T21:53:51Z http://eprints.utm.my/id/eprint/8750/ A new minimum pheromone threshold strategy (MPTS) for max-min ant system Wong, Kuan Yew See, Phen Chiak TJ Mechanical engineering and machinery In recent years, various metaheuristic approaches have been created to solve quadratic assignment problems (QAPs). Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. Although it has solved some QAPs successfully, it still contains some weaknesses and is unable to solve large QAP instances effectively. Thereafter, various suggestions have been made to improve the performance of the ACO algorithm. One of them is through the development of the max–min ant system (MMAS) algorithm. In this paper, a discussion will be given on the working structure of MMAS and its associated weaknesses or limitations. A new strategy that could further improve the search performance of MMAS will then be presented. Finally, the results of an experimental evaluation conducted to evaluate the usefulness of this new strategy will be described. Elsevier, The Netherlands 2009 Article PeerReviewed Wong, Kuan Yew and See, Phen Chiak (2009) A new minimum pheromone threshold strategy (MPTS) for max-min ant system. Applied Soft Computing, 9 (3). pp. 882-888. ISSN 1568-4946 http://dx.doi.org/10.1016/j.asoc.2008.11.011 doi:10.1016/j.asoc.2008.11.011 |
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TJ Mechanical engineering and machinery Wong, Kuan Yew See, Phen Chiak A new minimum pheromone threshold strategy (MPTS) for max-min ant system |
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In recent years, various metaheuristic approaches have been created to solve quadratic assignment problems (QAPs). Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. Although it has solved some QAPs successfully, it still contains some weaknesses and is unable to solve large QAP instances effectively. Thereafter, various suggestions have been made to improve the performance of the ACO algorithm. One of them is through the development of the max–min ant system (MMAS) algorithm. In this paper, a discussion will be given on the working structure of MMAS and its associated weaknesses or limitations. A new strategy that could further improve the search performance of MMAS will then be presented. Finally, the results of an experimental evaluation conducted to evaluate the usefulness of this new strategy will be described. |
| format |
Article |
| author |
Wong, Kuan Yew See, Phen Chiak |
| author_facet |
Wong, Kuan Yew See, Phen Chiak |
| author_sort |
Wong, Kuan Yew |
| title |
A new minimum pheromone threshold strategy (MPTS) for max-min ant system |
| title_short |
A new minimum pheromone threshold strategy (MPTS) for max-min ant system |
| title_full |
A new minimum pheromone threshold strategy (MPTS) for max-min ant system |
| title_fullStr |
A new minimum pheromone threshold strategy (MPTS) for max-min ant system |
| title_full_unstemmed |
A new minimum pheromone threshold strategy (MPTS) for max-min ant system |
| title_sort |
new minimum pheromone threshold strategy (mpts) for max-min ant system |
| publisher |
Elsevier, The Netherlands |
| publishDate |
2009 |
| url |
http://eprints.utm.my/id/eprint/8750/ http://dx.doi.org/10.1016/j.asoc.2008.11.011 |
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1732945374237163520 |