IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v190y2017icp146-157.html
   My bibliography  Save this article

A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm

Author

Listed:
  • Vitayasak, Srisatja
  • Pongcharoen, Pupong
  • Hicks, Chris

Abstract

Facility layout problems (FLP) involve determining the optimal placement of machines within a fixed space. An effective layout minimises costs. The total material travel distance is a key indicator of the efficiency of internal logistics. Changes in demand and product mix may alter the material flow. The dynamic facilities layout problem (DFLP) takes into account changes in demand and allows for the periodic redesign of facilities. Facility redesign may reduce the material flow cost, but there is a trade-off between material flow improvements and reorganisation costs. There is a limited literature on the redesign of facilities with stochastic demand, heterogeneous-sized resources and rectilinear material flow.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:proeco:v:190:y:2017:i:c:p:146-157
    DOI: 10.1016/j.ijpe.2016.03.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527316300743
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2016.03.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Nagar, Amit & Haddock, Jorge & Heragu, Sunderesh, 1995. "Multiple and bicriteria scheduling: A literature survey," European Journal of Operational Research, Elsevier, vol. 81(1), pages 88-104, February.
    2. Yu-Hsin Chen, Gary, 2013. "A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems," International Journal of Production Economics, Elsevier, vol. 142(2), pages 362-371.
    3. Modiri-Delshad, Mostafa & Rahim, Nasrudin Abd, 2014. "Solving non-convex economic dispatch problem via backtracking search algorithm," Energy, Elsevier, vol. 77(C), pages 372-381.
    4. Pongcharoen, P. & Hicks, C. & Braiden, P. M. & Stewardson, D. J., 2002. "Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products," International Journal of Production Economics, Elsevier, vol. 78(3), pages 311-322, August.
    5. 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.
    6. Pongcharoen, P. & Hicks, C. & Braiden, P. M., 2004. "The development of genetic algorithms for the finite capacity scheduling of complex products, with multiple levels of product structure," European Journal of Operational Research, Elsevier, vol. 152(1), pages 215-225, January.
    7. Montreuil, Benoit & Laforge, Andree, 1992. "Dynamic layout design given a scenario tree of probable futures," European Journal of Operational Research, Elsevier, vol. 63(2), pages 271-286, December.
    8. Chakraborty, Uday K. & Abbott, Travis E. & Das, Sajal K., 2012. "PEM fuel cell modeling using differential evolution," Energy, Elsevier, vol. 40(1), pages 387-399.
    9. Hicks, C., 2004. "A genetic algorithm tool for designing manufacturing facilities in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 90(2), pages 199-211, July.
    10. Gong, Wenyin & Cai, Zhihua, 2013. "Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution," Energy, Elsevier, vol. 59(C), pages 356-364.
    11. Dunker, Thomas & Radons, Gunter & Westkamper, Engelbert, 2005. "Combining evolutionary computation and dynamic programming for solving a dynamic facility layout problem," European Journal of Operational Research, Elsevier, vol. 165(1), pages 55-69, August.
    12. Hicks, Christian, 2006. "A Genetic Algorithm tool for optimising cellular or functional layouts in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 104(2), pages 598-614, December.
    13. Thepphakorn, Thatchai & Pongcharoen, Pupong & Hicks, Chris, 2014. "An ant colony based timetabling tool," International Journal of Production Economics, Elsevier, vol. 149(C), pages 131-144.
    14. Yang, Taho & Peters, Brett A., 1998. "Flexible machine layout design for dynamic and uncertain production environments," European Journal of Operational Research, Elsevier, vol. 108(1), pages 49-64, July.
    15. Baykasoglu, Adil & Dereli, Turkay & Sabuncu, Ibrahim, 2006. "An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems," Omega, Elsevier, vol. 34(4), pages 385-396, August.
    16. Krishna K. Krishnan & S. Hossein Cheraghi & Chandan N. Nayak, 2008. "Facility layout design for multiple production scenarios in a dynamic environment," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 3(2), pages 105-133.
    17. 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. Pablo Pérez-Gosende & Josefa Mula & Manuel Díaz-Madroñero, 2020. "Overview of Dynamic Facility Layout Planning as a Sustainability Strategy," Sustainability, MDPI, vol. 12(19), pages 1-16, October.
    2. Siyu Xu & Yufei Wang & Xiao Feng, 2020. "Plant Layout Optimization for Chemical Industry Considering Inner Frame Structure Design," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    3. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2019. "Reliable single-allocation hub location problem with disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 90-120.
    4. Hassan, Bryar A. & Rashid, Tarik A., 2020. "Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    5. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2021. "3D facility layout problem," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1065-1090, April.

    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. Bock, Stefan & Hoberg, Kai, 2007. "Detailed layout planning for irregularly-shaped machines with transportation path design," European Journal of Operational Research, Elsevier, vol. 177(2), pages 693-718, March.
    2. Pongcharoen, P. & Promtet, W. & Yenradee, P. & Hicks, C., 2008. "Stochastic Optimisation Timetabling Tool for university course scheduling," International Journal of Production Economics, Elsevier, vol. 112(2), pages 903-918, April.
    3. 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.
    4. Dunker, Thomas & Radons, Gunter & Westkamper, Engelbert, 2005. "Combining evolutionary computation and dynamic programming for solving a dynamic facility layout problem," European Journal of Operational Research, Elsevier, vol. 165(1), pages 55-69, August.
    5. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    6. Xu, Shuhui & Wang, Yong & Wang, Zhi, 2019. "Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method," Energy, Elsevier, vol. 173(C), pages 457-467.
    7. Priya, K. & Sathishkumar, K. & Rajasekar, N., 2018. "A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 121-144.
    8. Balakrishnan, Jaydeep & Cheng, Chun Hung, 2007. "Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions," European Journal of Operational Research, Elsevier, vol. 177(1), pages 281-309, February.
    9. Gouda, Eid A. & Kotb, Mohamed F. & El-Fergany, Attia A., 2021. "Jellyfish search algorithm for extracting unknown parameters of PEM fuel cell models: Steady-state performance and analysis," Energy, Elsevier, vol. 221(C).
    10. Song, Dong-Ping, 2006. "Raw material release time control for complex make-to-order products with stochastic processing times," International Journal of Production Economics, Elsevier, vol. 103(1), pages 371-385, September.
    11. Haral, Uday & Chen, Rew-Win & Ferrell, William Jr & Kurz, Mary Beth, 2007. "Multiobjective single machine scheduling with nontraditional requirements," International Journal of Production Economics, Elsevier, vol. 106(2), pages 574-584, April.
    12. Hicks, Christian, 2006. "A Genetic Algorithm tool for optimising cellular or functional layouts in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 104(2), pages 598-614, December.
    13. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    14. Miao, Di & Chen, Wei & Zhao, Wei & Demsas, Tekle, 2020. "Parameter estimation of PEM fuel cells employing the hybrid grey wolf optimization method," Energy, Elsevier, vol. 193(C).
    15. McGovern, T. & Hicks, C., 2004. "Deregulation and restructuring of the global electricity supply industry and its impact upon power plant suppliers," International Journal of Production Economics, Elsevier, vol. 89(3), pages 321-337, June.
    16. Gong, Wenyin & Yan, Xuesong & Liu, Xiaobo & Cai, Zhihua, 2015. "Parameter extraction of different fuel cell models with transferred adaptive differential evolution," Energy, Elsevier, vol. 86(C), pages 139-151.
    17. Akash Tayal & Surya Prakash Singh, 2018. "Integrating big data analytic and hybrid firefly-chaotic simulated annealing approach for facility layout problem," Annals of Operations Research, Springer, vol. 270(1), pages 489-514, November.
    18. Eben-Chaime, Moshe & Bechar, Avital & Baron, Ana, 2011. "Economical evaluation of greenhouse layout design," International Journal of Production Economics, Elsevier, vol. 134(1), pages 246-254, November.
    19. 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.
    20. Hicks, C., 2004. "A genetic algorithm tool for designing manufacturing facilities in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 90(2), pages 199-211, July.

    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:proeco:v:190:y:2017:i:c:p:146-157. 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/ijpe .

    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.