A technique for improving the Max-Min Ant System algorithm

Phen Chiak See, Kuan Yew Wong, Komarudin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08
Subtitle of host publicationGlobal Links for Human Development
Pages863-866
Number of pages4
DOIs
Publication statusPublished - 2008
EventInternational Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development - Kuala Lumpur, Malaysia
Duration: 13 May 200815 May 2008

Publication series

NameProceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development

Conference

ConferenceInternational Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development
Country/TerritoryMalaysia
CityKuala Lumpur
Period13/05/0815/05/08

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