IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v204y2010i3p463-472.html
   My bibliography  Save this article

Extensions to STaTS for practical applications of the facility layout problem

Author

Listed:
  • Scholz, Daniel
  • Jaehn, Florian
  • Junker, Andreas

Abstract

We consider a very general case of the facility layout problem, which allows incorporating various aspects appearing in real life applications. These aspects include loose requirements on facilities' footprints, each of which only needs to be of rectangular shape and can optionally be restricted concerning the surface area or the aspect ratio. Compared to former approaches other generalizations of practical relevance are multiple, not necessarily rectangular workshops, exclusion zones in workshops, predefined positions of facilities, the consideration of aisles, and the adherence of further restrictions such as the enforced placement of certain facilities next to an exterior wall or a minimum distance between certain pairs of facilities. Although different objectives could be applied, we especially focus on the most relevant one in practice, the minimization of transportation costs. We show that this problem can heuristically be solved using an extension of the Slicing Tree and Tabu Search (STaTS) based approach. The application of this algorithm on practical data shows its effectiveness. The paper concludes with a step-by-step guide for the application of STaTS in practice.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:204:y:2010:i:3:p:463-472
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00862-5
    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. Goetschalckx, Marc, 1992. "An interactive layout heuristic based on hexagonal adjacency graphs," European Journal of Operational Research, Elsevier, vol. 63(2), pages 304-321, December.
    2. 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.
    3. 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.
    4. 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).
    5. Kar Yan Tam, 1992. "Genetic algorithms, function optimization, and facility layout design," European Journal of Operational Research, Elsevier, vol. 63(2), pages 322-346, December.
    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. 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.
    2. 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.

    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. 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. 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.
    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. McKendall Jr., Alan R. & Hakobyan, Artak, 2010. "Heuristics for the dynamic facility layout problem with unequal-area departments," European Journal of Operational Research, Elsevier, vol. 201(1), pages 171-182, February.
    13. 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.
    14. Ali, Agha Iqbal & O'Connor, Debra J., 2010. "The impact of distribution system characteristics on computational tractability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 323-333, January.
    15. Carrizosa, Emilio & Guerrero, Vanesa & Romero Morales, Dolores, 2018. "On Mathematical Optimization for the visualization of frequencies and adjacencies as rectangular maps," European Journal of Operational Research, Elsevier, vol. 265(1), pages 290-302.
    16. Vitayasak, Srisatja & Pongcharoen, Pupong & Hicks, Chris, 2017. "A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm," International Journal of Production Economics, Elsevier, vol. 190(C), pages 146-157.
    17. Gomez, A. & Fernandez, Q. I. & De la Fuente Garcia, D. & Garcia, P. J., 2003. "Using genetic algorithms to resolve layout problems in facilities where there are aisles," International Journal of Production Economics, Elsevier, vol. 84(3), pages 271-282, June.
    18. Vila Goncalves Filho, Eduardo & Jose Tiberti, Alexandre, 2006. "A group genetic algorithm for the machine cell formation problem," International Journal of Production Economics, Elsevier, vol. 102(1), pages 1-21, July.
    19. Germán Herrera Vidal & Jairo R. Coronado-Hernández & Claudia Minnaard, 2023. "Measuring manufacturing system complexity: a literature review," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 2865-2888, October.
    20. 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.

    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:204:y:2010:i:3:p:463-472. 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.