An improved ant system algorithm for unequal area facility layout problems

To date, a formal Ant Colony Optimization (ACO) based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This study proposes an Ant System (AS) algorithm for solving UA-FLPs using the Flexible Bay Structure (FBS) representation. In addition, this study pr...

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Main Author: Komarudin, Komarudin
Format: Thesis
Language:English
Published: 2009
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Online Access:http://eprints.utm.my/id/eprint/11342/6/KomarudinMFKM2009.pdf
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spelling my-utm-ep.113422017-09-20T10:42:16Z An improved ant system algorithm for unequal area facility layout problems 2009-10 Komarudin, Komarudin TJ Mechanical engineering and machinery To date, a formal Ant Colony Optimization (ACO) based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This study proposes an Ant System (AS) algorithm for solving UA-FLPs using the Flexible Bay Structure (FBS) representation. In addition, this study proposes an improvement to the FBS representation when solving problems which have empty spaces. The proposed algorithm uses several types of local search to improve its search performance. It was extensively tested using 20 well-known problem instances taken from the literature. The proposed algorithm is effective and can produce all of the best FBS solutions (or even better) except for 2 problem instances. In addition, it can improve the best-known solution for 7 problem instances. The improvement gained by the proposed algorithm is up to 21.36% compared to previous research. Evidently, the proposed algorithm is also proven to be effective when solving large problem sets with 20, 25, and 30 departments. Furthermore, this study has implemented a Fuzzy Logic Controller (FLC) to automate the tuning of the AS algorithm. The experiments involved tuning four parameters individually, i.e. number of ants, pheromone information parameter, heuristic information parameter, and evaporation rate, as well as tuning all of them at once. The results showed that FLC could be used to replace manual parameter tuning which is time consuming. The results also showed that instead of using static parameter values, FLC has the potential to help the AS algorithm to achieve better objective function values. 2009-10 Thesis http://eprints.utm.my/id/eprint/11342/ http://eprints.utm.my/id/eprint/11342/6/KomarudinMFKM2009.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering 1. Wong, K.Y., Ahmad, R. and Komarudin. (2007). An evaluation of parameters tuning methods in metaheuristic algorithms. Proceedings of the Regional Conference on Advanced Processes and Systems in Manufacturing. Putrajaya, Malaysia, pp.41-48. 2. Wong, K.Y. and Komarudin. (2008). Parameter tuning for ant colony optimization: a review. Proceedings of the International Conference on Computer and Communication Engineering. Kuala Lumpur, Malaysia, pp.542-545. 3. Wong, K.Y. and Komarudin. (2008). Ant colony optimization in solving facility layout problems. Proceedings of the International Conference on Mechanical and Manufacturing Engineering. Johor Bahru, Malaysia. 4. Komarudin and Wong, K.Y. (2009). Applying Ant System for Solving Unequal Area Facility Layout Problems. Accepted for publication in European Journal of Operational Research. 5. Komarudin, Wong, K.Y., and See, P. C. (2009). Solving Facility Layout Problems using Flexible Bay Structure Representation and Ant System Algorithm. Submitted to Expert Systems with Applications. 6. Wong, K.Y. and Komarudin. (2010). Comparison of Techniques for Dealing with Empty Spaces in Unequal Area Facility Layout Problems. Accepted for publication in International Journal of Industrial and Systems Engineering, Vol.6, No.3.
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Komarudin, Komarudin
An improved ant system algorithm for unequal area facility layout problems
description To date, a formal Ant Colony Optimization (ACO) based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This study proposes an Ant System (AS) algorithm for solving UA-FLPs using the Flexible Bay Structure (FBS) representation. In addition, this study proposes an improvement to the FBS representation when solving problems which have empty spaces. The proposed algorithm uses several types of local search to improve its search performance. It was extensively tested using 20 well-known problem instances taken from the literature. The proposed algorithm is effective and can produce all of the best FBS solutions (or even better) except for 2 problem instances. In addition, it can improve the best-known solution for 7 problem instances. The improvement gained by the proposed algorithm is up to 21.36% compared to previous research. Evidently, the proposed algorithm is also proven to be effective when solving large problem sets with 20, 25, and 30 departments. Furthermore, this study has implemented a Fuzzy Logic Controller (FLC) to automate the tuning of the AS algorithm. The experiments involved tuning four parameters individually, i.e. number of ants, pheromone information parameter, heuristic information parameter, and evaporation rate, as well as tuning all of them at once. The results showed that FLC could be used to replace manual parameter tuning which is time consuming. The results also showed that instead of using static parameter values, FLC has the potential to help the AS algorithm to achieve better objective function values.
format Thesis
qualification_level Master's degree
author Komarudin, Komarudin
author_facet Komarudin, Komarudin
author_sort Komarudin, Komarudin
title An improved ant system algorithm for unequal area facility layout problems
title_short An improved ant system algorithm for unequal area facility layout problems
title_full An improved ant system algorithm for unequal area facility layout problems
title_fullStr An improved ant system algorithm for unequal area facility layout problems
title_full_unstemmed An improved ant system algorithm for unequal area facility layout problems
title_sort improved ant system algorithm for unequal area facility layout problems
granting_institution Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department Faculty of Mechanical Engineering
publishDate 2009
url http://eprints.utm.my/id/eprint/11342/6/KomarudinMFKM2009.pdf
_version_ 1747814840162844672