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...

Full description

Saved in:

Bibliographic Details
Main Author:	Komarudin, Komarudin
Format:	Thesis
Language:	English
Published:	2009
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.utm.my/id/eprint/11342/6/KomarudinMFKM2009.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.11342
record_format	uketd_dc
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

An improved ant system algorithm for unequal area facility layout problems

Similar Items