A technique for improving the Max-Min Ant System algorithm

Author

Chiak See, Phen ; Yew Wong, Kuan ; Komarudin

Author_Institution

Dept. of Manuf. & Ind. Eng., Univ. Teknol. Malaysia, Skudai

fYear

2008

fDate

13-15 May 2008

Firstpage

863

Lastpage

866

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.

Keywords

distributed algorithms; heuristic programming; optimisation; ant colony optimization; distributed algorithms; max-min ant system algorithm; metaheuristic approaches; quadratic assignment problems; Ant colony optimization; Collaboration; Computer aided manufacturing; Distributed algorithms; Heuristic algorithms; Industrial engineering; Mechanical engineering; Sampling methods; Scheduling algorithm; Turing machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Communication Engineering, 2008. ICCCE 2008. International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-1691-2

Electronic_ISBN

978-1-4244-1692-9

Type

conf

DOI

10.1109/ICCCE.2008.4580728

Filename

4580728