IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v202y2010i3p730-746.html
   My bibliography  Save this article

Applying Ant System for solving Unequal Area Facility Layout Problems

Author

Listed:
  • Komarudin
  • Wong, Kuan Yew

Abstract

Ant Colony Optimization (ACO) is a young metaheuristic algorithm which has shown promising results in solving many optimization problems. To date, a formal ACO-based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This paper proposes an Ant System (AS) (one of the ACO variants) to solve them. As a discrete optimization algorithm, the proposed algorithm uses slicing tree representation to easily represent the problems without too restricting the solution space. It uses several types of local search to improve its search performance. It is then tested using several case problems with different size and setting. Overall, the proposed algorithm shows encouraging results in solving UA-FLPs.

Suggested Citation

  • Komarudin & Wong, Kuan Yew, 2010. "Applying Ant System for solving Unequal Area Facility Layout Problems," European Journal of Operational Research, Elsevier, vol. 202(3), pages 730-746, May.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:3:p:730-746
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00483-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hani, Y. & Amodeo, L. & Yalaoui, F. & Chen, H., 2007. "Ant colony optimization for solving an industrial layout problem," European Journal of Operational Research, Elsevier, vol. 183(2), pages 633-642, December.
    2. van Camp, Drew J. & Carter, Michael W. & Vannelli, Anthony, 1992. "A nonlinear optimization approach for solving facility layout problems," European Journal of Operational Research, Elsevier, vol. 57(2), pages 174-189, March.
    3. Gordon C. Armour & Elwood S. Buffa, 1963. "A Heuristic Algorithm and Simulation Approach to Relative Location of Facilities," Management Science, INFORMS, vol. 9(2), pages 294-309, January.
    4. Phen Chiak See & Kuan Yew Wong, 2008. "Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 3(6), pages 644-672.
    5. Scholz, Daniel & Petrick, Anita & Domschke, Wolfgang, 2009. "STaTS: A Slicing Tree and Tabu Search based heuristic for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 166-178, August.
    6. Kuan Yew Wong & Phen Chiak See, 2009. "A genetic ant colony optimisation system (GenANT) for quadratic assignment problems," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 1(4), pages 456-475.
    7. Hanif D. Sherali & Barbara M. P. Fraticelli & Russell D. Meller, 2003. "Enhanced Model Formulations for Optimal Facility Layout," Operations Research, INFORMS, vol. 51(4), pages 629-644, August.
    8. Scholz, Daniel & Petrick, Anita & Domschke, Wolfgang, 2009. "STaTS: A Slicing Tree and Tabu Search based heuristic for the unequal area facility layout problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 39430, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anjos, Miguel F. & Vieira, Manuel V.C., 2017. "Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions," European Journal of Operational Research, Elsevier, vol. 261(1), pages 1-16.
    2. Liu, Jingfa & Wang, Dawen & He, Kun & Xue, Yu, 2017. "Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1052-1063.
    3. Ali Derakhshan Asl & Kuan Yew Wong & Manoj Kumar Tiwari, 2016. "Unequal-area stochastic facility layout problems: solutions using improved covariance matrix adaptation evolution strategy, particle swarm optimisation, and genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 799-823, February.
    4. Bozer, Yavuz A. & Wang, Chi-Tai, 2012. "A graph-pair representation and MIP-model-based heuristic for the unequal-area facility layout problem," European Journal of Operational Research, Elsevier, vol. 218(2), pages 382-391.
    5. Jerzy Grobelny & Rafal Michalski, 2017. "A novel version of simulated annealing based on linguistic patterns for solving facility layout problems," WORking papers in Management Science (WORMS) WORMS/17/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    6. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2020. "A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 615-640, March.
    7. Paes, Frederico Galaxe & Pessoa, Artur Alves & Vidal, Thibaut, 2017. "A hybrid genetic algorithm with decomposition phases for the Unequal Area Facility Layout Problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 742-756.
    8. Kulturel-Konak, Sadan, 2012. "A linear programming embedded probabilistic tabu search for the unequal-area facility layout problem with flexible bays," European Journal of Operational Research, Elsevier, vol. 223(3), pages 614-625.
    9. Minhee Kim & Junjae Chae, 2019. "Monarch Butterfly Optimization for Facility Layout Design Based on a Single Loop Material Handling Path," Mathematics, MDPI, vol. 7(2), pages 1-21, February.
    10. Gonçalves, José Fernando & Resende, Mauricio G.C., 2015. "A biased random-key genetic algorithm for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 246(1), pages 86-107.
    11. Li, Jinhua & Smith, Alice E., 2018. "Block layout for attraction-based enterprises," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1100-1112.
    12. Jingyang Zhou & Peter E.D. Love & Kok Lay Teo & Hanbin Luo, 2017. "An exact penalty function method for optimising QAP formulation in facility layout problem," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2913-2929, May.
    13. Asef-Vaziri, Ardavan & Jahandideh, Hossein & Modarres, Mohammad, 2017. "Loop-based facility layout design under flexible bay structures," International Journal of Production Economics, Elsevier, vol. 193(C), pages 713-725.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gonçalves, José Fernando & Resende, Mauricio G.C., 2015. "A biased random-key genetic algorithm for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 246(1), pages 86-107.
    2. Bozer, Yavuz A. & Wang, Chi-Tai, 2012. "A graph-pair representation and MIP-model-based heuristic for the unequal-area facility layout problem," European Journal of Operational Research, Elsevier, vol. 218(2), pages 382-391.
    3. Minhee Kim & Junjae Chae, 2019. "Monarch Butterfly Optimization for Facility Layout Design Based on a Single Loop Material Handling Path," Mathematics, MDPI, vol. 7(2), pages 1-21, February.
    4. Anjos, Miguel F. & Vieira, Manuel V.C., 2017. "Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions," European Journal of Operational Research, Elsevier, vol. 261(1), pages 1-16.
    5. Asef-Vaziri, Ardavan & Jahandideh, Hossein & Modarres, Mohammad, 2017. "Loop-based facility layout design under flexible bay structures," International Journal of Production Economics, Elsevier, vol. 193(C), pages 713-725.
    6. Kulturel-Konak, Sadan, 2012. "A linear programming embedded probabilistic tabu search for the unequal-area facility layout problem with flexible bays," European Journal of Operational Research, Elsevier, vol. 223(3), pages 614-625.
    7. Mehmet Burak Şenol & Ekrem Alper Murat, 2023. "A sequential solution heuristic for continuous facility layout problems," Annals of Operations Research, Springer, vol. 320(1), pages 355-377, January.
    8. Scholz, Daniel & Jaehn, Florian & Junker, Andreas, 2010. "Extensions to STaTS for practical applications of the facility layout problem," European Journal of Operational Research, Elsevier, vol. 204(3), pages 463-472, August.
    9. Xie, Yue & Zhou, Shenghan & Xiao, Yiyong & Kulturel-Konak, Sadan & Konak, Abdullah, 2018. "A β-accurate linearization method of Euclidean distance for the facility layout problem with heterogeneous distance metrics," European Journal of Operational Research, Elsevier, vol. 265(1), pages 26-38.
    10. Emde, Simon & Boysen, Nils, 2012. "Optimally locating in-house logistics areas to facilitate JIT-supply of mixed-model assembly lines," International Journal of Production Economics, Elsevier, vol. 135(1), pages 393-402.
    11. I. Jerin Leno & S. Saravana Sankar & S. G. Ponnambalam, 2018. "MIP model and elitist strategy hybrid GA–SA algorithm for layout design," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 369-387, February.
    12. Paes, Frederico Galaxe & Pessoa, Artur Alves & Vidal, Thibaut, 2017. "A hybrid genetic algorithm with decomposition phases for the Unequal Area Facility Layout Problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 742-756.
    13. Scholz, Daniel & Petrick, Anita & Domschke, Wolfgang, 2009. "STaTS: A Slicing Tree and Tabu Search based heuristic for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 166-178, August.
    14. Miguel F. Anjos & Anthony Vannelli, 2006. "A New Mathematical-Programming Framework for Facility-Layout Design," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 111-118, February.
    15. Lin, Jin-Ling & Foote, Bobbie & Pulat, Simin & Chang, Chir-Ho & Cheung, John Y., 1996. "Solving the failure-to-fit problem for plant layout: By changing department shapes and sizes," European Journal of Operational Research, Elsevier, vol. 89(1), pages 135-146, February.
    16. Lee, Geun-Cheol & Kim, Yeong-Dae, 2000. "Algorithms for adjusting shapes of departments in block layouts on the grid-based plane," Omega, Elsevier, vol. 28(1), pages 111-122, February.
    17. Bolte, Andreas & Thonemann, Ulrich Wilhelm, 1996. "Optimizing simulated annealing schedules with genetic programming," European Journal of Operational Research, Elsevier, vol. 92(2), pages 402-416, July.
    18. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2020. "A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 615-640, March.
    19. Zhongwei Zhang & Lihui Wu & Zhaoyun Wu & Wenqiang Zhang & Shun Jia & Tao Peng, 2022. "Energy-Saving Oriented Manufacturing Workshop Facility Layout: A Solution Approach Using Multi-Objective Particle Swarm Optimization," Sustainability, MDPI, vol. 14(5), pages 1-28, February.
    20. E A Silver, 2004. "An overview of heuristic solution methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 936-956, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:202:y:2010:i:3:p:730-746. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.