IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v49y2014icp30-41.html
   My bibliography  Save this article

Planning of a decentralized distribution network using bilevel optimization

Author

Listed:
  • Calvete, Herminia I.
  • Galé, Carmen
  • Iranzo, José A.

Abstract

This paper proposes a bilevel optimization problem to model the planning of a distribution network that allows us to take into account how decisions made at the distribution stage of the supply chain can affect and be affected by decisions made at the manufacturing stage. Usually, the distribution network design problem decides on the opening of depots and the distribution from the depots to customers only and pays no attention to the manufacturing process itself. By way of example, the paper discusses the implications of formulating a bilevel model to integrate distribution and manufacturing, maintaining the hierarchy existing in the decision process. The resulting model is a bilevel mixed integer optimization problem. Hence, only small instances can be optimally solved in an acceptable computing time. In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed. The algorithm combines the use of an evolutionary algorithm to control the supply of depots with optimization techniques to determine the delivery from depots to customers and the supply from manufacturing plants to depots. A computational experiment is carried out to assess the efficiency and robustness of the algorithm.

Suggested Citation

  • Calvete, Herminia I. & Galé, Carmen & Iranzo, José A., 2014. "Planning of a decentralized distribution network using bilevel optimization," Omega, Elsevier, vol. 49(C), pages 30-41.
    • Handle: RePEc:eee:jomega:v:49:y:2014:i:c:p:30-41
    DOI: 10.1016/j.omega.2014.05.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048314000668
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2014.05.004?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. Cao, Dong & Chen, Mingyuan, 2006. "Capacitated plant selection in a decentralized manufacturing environment: A bilevel optimization approach," European Journal of Operational Research, Elsevier, vol. 169(1), pages 97-110, February.
    2. Sabri, Ehap H. & Beamon, Benita M., 2000. "A multi-objective approach to simultaneous strategic and operational planning in supply chain design," Omega, Elsevier, vol. 28(5), pages 581-598, October.
    3. Herminia Calvete & Carmen Galé & Stephan Dempe & Sebastian Lohse, 2012. "Bilevel problems over polyhedra with extreme point optimal solutions," Journal of Global Optimization, Springer, vol. 53(3), pages 573-586, July.
    4. Christofides, N. & Beasley, J. E., 1983. "Extensions to a Lagrangean relaxation approach for the capacitated warehouse location problem," European Journal of Operational Research, Elsevier, vol. 12(1), pages 19-28, January.
    5. Umit Akinc & Basheer M. Khumawala, 1977. "An Efficient Branch and Bound Algorithm for the Capacitated Warehouse Location Problem," Management Science, INFORMS, vol. 23(6), pages 585-594, February.
    6. Liu, Songsong & Papageorgiou, Lazaros G., 2013. "Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry," Omega, Elsevier, vol. 41(2), pages 369-382.
    7. Alfred A. Kuehn & Michael J. Hamburger, 1963. "A Heuristic Program for Locating Warehouses," Management Science, INFORMS, vol. 9(4), pages 643-666, July.
    8. Kopanos, Georgios M. & Puigjaner, Luis & Georgiadis, Michael C., 2012. "Simultaneous production and logistics operations planning in semicontinuous food industries," Omega, Elsevier, vol. 40(5), pages 634-650.
    9. Mula, Josefa & Peidro, David & Díaz-Madroñero, Manuel & Vicens, Eduardo, 2010. "Mathematical programming models for supply chain production and transport planning," European Journal of Operational Research, Elsevier, vol. 204(3), pages 377-390, August.
    10. Sainathuni, Bhanuteja & Parikh, Pratik J. & Zhang, Xinhui & Kong, Nan, 2014. "The warehouse-inventory-transportation problem for supply chains," European Journal of Operational Research, Elsevier, vol. 237(2), pages 690-700.
    11. Verdecho, María-José & Alfaro-Saiz, Juan-Jose & Rodriguez-Rodriguez, Raul & Ortiz-Bas, Angel, 2012. "A multi-criteria approach for managing inter-enterprise collaborative relationships," Omega, Elsevier, vol. 40(3), pages 249-263.
    12. Pan, Feng & Nagi, Rakesh, 2013. "Multi-echelon supply chain network design in agile manufacturing," Omega, Elsevier, vol. 41(6), pages 969-983.
    13. Gregor Dudek, 2009. "Collaborative Planning in Supply Chains," Springer Books, Springer, number 978-3-540-92176-9, September.
    14. Jayaraman, Vaidyanathan & Pirkul, Hasan, 2001. "Planning and coordination of production and distribution facilities for multiple commodities," European Journal of Operational Research, Elsevier, vol. 133(2), pages 394-408, January.
    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. Nishizaki, Ichiro & Hayashida, Tomohiro & Sekizaki, Shinya & Okabe, Junya, 2022. "Data envelopment analysis approaches for two-level production and distribution planning problems," European Journal of Operational Research, Elsevier, vol. 300(1), pages 255-268.
    2. Sun, X.T. & Chung, S.H. & Chan, Felix T.S., 2015. "Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 110-127.
    3. Zhou, Xiaoyang & Luo, Rui & Tu, Yan & Lev, Benjamin & Pedrycz, Witold, 2018. "Data envelopment analysis for bi-level systems with multiple followers," Omega, Elsevier, vol. 77(C), pages 180-188.
    4. Marjia Haque & Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam, 2022. "A combined approach for modeling multi-echelon multi-period decentralized supply chain," Annals of Operations Research, Springer, vol. 315(2), pages 1665-1702, August.
    5. Herminia I. Calvete & Carmen Galé & José A. Iranzo, 2016. "An improved evolutionary algorithm for the two-stage transportation problem with fixed charge at depots," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(1), pages 189-206, January.
    6. Wang, Delu & Liu, Yifei & Wang, Yadong & Shi, Xunpeng & Song, Xuefeng, 2020. "Allocation of coal de-capacity quota among provinces in China: A bi-level multi-objective combinatorial optimization approach," Energy Economics, Elsevier, vol. 87(C).
    7. Abdul Sattar Safaei & Saba Farsad & Mohammad Mahdi Paydar, 2020. "Emergency logistics planning under supply risk and demand uncertainty," Operational Research, Springer, vol. 20(3), pages 1437-1460, September.

    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. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "Tactical supply chain planning models with inherent flexibility: definition and review," Annals of Operations Research, Springer, vol. 244(2), pages 407-427, September.
    2. Klaus Büdenbender & Tore Grünert & Hans-Jürgen Sebastian, 2000. "A Hybrid Tabu Search/Branch-and-Bound Algorithm for the Direct Flight Network Design Problem," Transportation Science, INFORMS, vol. 34(4), pages 364-380, November.
    3. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Fathali Firoozi, 2008. "Boundary Distributions in Testing Inequality Hypotheses," Working Papers 0046, College of Business, University of Texas at San Antonio.
    5. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "A tactical supply chain planning model with multiple flexibility options: an empirical evaluation," Annals of Operations Research, Springer, vol. 244(2), pages 429-454, September.
    6. Turan Paksoy & Eren Özceylan & Gerhard-Wilhelm Weber, 2013. "Profit oriented supply chain network optimization," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(2), pages 455-478, March.
    7. Liu, Songsong & Papageorgiou, Lazaros G., 2013. "Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry," Omega, Elsevier, vol. 41(2), pages 369-382.
    8. Hêris Golpîra, 2017. "Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 21-41.
    9. Sağlam, Ümit & Banerjee, Avijit, 2018. "Integrated multiproduct batch production and truck shipment scheduling under different shipping policies," Omega, Elsevier, vol. 74(C), pages 70-81.
    10. Hashem Omrani & Farzane Adabi & Narges Adabi, 2017. "Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 816-828, July.
    11. Longinidis, Pantelis & Georgiadis, Michael C., 2014. "Integration of sale and leaseback in the optimal design of supply chain networks," Omega, Elsevier, vol. 47(C), pages 73-89.
    12. Melkote, Sanjay & Daskin, Mark S., 2001. "Capacitated facility location/network design problems," European Journal of Operational Research, Elsevier, vol. 129(3), pages 481-495, March.
    13. Al-Husain, Raed & Khorramshahgol, Reza, 2020. "Incorporating analytical hierarchy process and goal programming to design responsive and efficient supply chains," Operations Research Perspectives, Elsevier, vol. 7(C).
    14. Harkness, Joseph & ReVelle, Charles, 2003. "Facility location with increasing production costs," European Journal of Operational Research, Elsevier, vol. 145(1), pages 1-13, February.
    15. Emelogu, Adindu & Chowdhury, Sudipta & Marufuzzaman, Mohammad & Bian, Linkan & Eksioglu, Burak, 2016. "An enhanced sample average approximation method for stochastic optimization," International Journal of Production Economics, Elsevier, vol. 182(C), pages 230-252.
    16. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    17. Klose, Andreas & Gortz, Simon, 2007. "A branch-and-price algorithm for the capacitated facility location problem," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1109-1125, June.
    18. Chan, Chi Kin & Lee, Y.C.E. & Campbell, J.F., 2013. "Environmental performance—Impacts of vendor–buyer coordination," International Journal of Production Economics, Elsevier, vol. 145(2), pages 683-695.
    19. Wei, Wenchao & Guimarães, Luis & Amorim, Pedro & Almada-Lobo, Bernardo, 2017. "Tactical production and distribution planning with dependency issues on the production process," Omega, Elsevier, vol. 67(C), pages 99-114.
    20. Sharma, R.R.K. & Berry, V., 2007. "Developing new formulations and relaxations of single stage capacitated warehouse location problem (SSCWLP): Empirical investigation for assessing relative strengths and computational effort," European Journal of Operational Research, Elsevier, vol. 177(2), pages 803-812, March.

    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:jomega:v:49:y:2014:i:c:p:30-41. 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/wps/find/journaldescription.cws_home/375/description#description .

    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.