IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v60y2014icp66-84.html
   My bibliography  Save this article

Metaheuristic procedure for a bi-objective supply chain design problem with uncertainty

Author

Listed:
  • Cardona-Valdés, Y.
  • Álvarez, A.
  • Pacheco, J.

Abstract

We consider the design of a two echelon production distribution network with multiple manufacturing plants, distribution centers (DC’s) and a set of candidate warehouses. One of the main contributions of the study is to extend the existing literature by incorporating the demand uncertainty of DC’s within the warehouse location and transportation mode allocation decisions, as well as providing a network design satisfying the both economical and service quality objectives of the decision maker within two echelon supply network setting. In order to take into account the effects of the uncertainty we apply an scenario-based approach and a two-stage stochastic problem is formulated in order to minimize total cost and total service time, simultaneously. Another important contribution is the development of a solution procedure for this bi-objective stochastic problem by applying tabu search within the framework of Multi-objective Adaptive Memory Programming. Results are compared with the optimal Pareto fronts obtained for small instances using the ∊-constraint method and standard branch and bound techniques. Numerical results demonstrate the computational effectiveness of the algorithm proposed. Finally, we include some results that confirm the convenience of including the randomness in the demand parameter.

Suggested Citation

  • Cardona-Valdés, Y. & Álvarez, A. & Pacheco, J., 2014. "Metaheuristic procedure for a bi-objective supply chain design problem with uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 66-84.
    • Handle: RePEc:eee:transb:v:60:y:2014:i:c:p:66-84
    DOI: 10.1016/j.trb.2013.11.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261513002191
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2013.11.010?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. Moncayo-Martínez, Luis A. & Zhang, David Z., 2011. "Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design," International Journal of Production Economics, Elsevier, vol. 131(1), pages 407-420, May.
    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. Olivares-Benitez, Elias & Ríos-Mercado, Roger Z. & González-Velarde, José Luis, 2013. "A metaheuristic algorithm to solve the selection of transportation channels in supply chain design," International Journal of Production Economics, Elsevier, vol. 145(1), pages 161-172.
    4. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    5. Tragantalerngsak, Suda & Holt, John & Ronnqvist, Mikael, 2000. "An exact method for the two-echelon, single-source, capacitated facility location problem," European Journal of Operational Research, Elsevier, vol. 123(3), pages 473-489, June.
    6. Caballero, Rafael & Gonzalez, Mercedes & Guerrero, Flor M & Molina, Julian & Paralera, Concepcion, 2007. "Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1751-1763, March.
    7. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    8. Afshin Mansouri, S. & Gallear, David & Askariazad, Mohammad H., 2012. "Decision support for build-to-order supply chain management through multiobjective optimization," International Journal of Production Economics, Elsevier, vol. 135(1), pages 24-36.
    9. Peng, Peng & Snyder, Lawrence V. & Lim, Andrew & Liu, Zuli, 2011. "Reliable logistics networks design with facility disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1190-1211, September.
    10. Samir Elhedhli & Jean-Louis Goffin, 2005. "Efficient Production-Distribution System Design," Management Science, INFORMS, vol. 51(7), pages 1151-1164, July.
    11. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    12. Perugia, Alessandro & Moccia, Luigi & Cordeau, Jean-François & Laporte, Gilbert, 2011. "Designing a home-to-work bus service in a metropolitan area," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1710-1726.
    13. Berg, J. P. van den & Zijm, W. H. M., 1999. "Models for warehouse management: Classification and examples," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 519-528, March.
    14. Listes, Ovidiu & Dekker, Rommert, 2005. "A stochastic approach to a case study for product recovery network design," European Journal of Operational Research, Elsevier, vol. 160(1), pages 268-287, January.
    15. Joaquín Pacheco & Rafael Caballero & Manuel Laguna & Julián Molina, 2013. "Bi-Objective Bus Routing: An Application to School Buses in Rural Areas," Transportation Science, INFORMS, vol. 47(3), pages 397-411, August.
    16. Belarmino Adenso-Díaz & Manuel Laguna, 2006. "Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search," Operations Research, INFORMS, vol. 54(1), pages 99-114, February.
    17. Jayaraman, Vaidyanathan & Patterson, Raymond A. & Rolland, Erik, 2003. "The design of reverse distribution networks: Models and solution procedures," European Journal of Operational Research, Elsevier, vol. 150(1), pages 128-149, October.
    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. Mosahar Tarimoradi & M. H. Fazel Zarandi & Hosain Zaman & I. B. Turksan, 2017. "Evolutionary fuzzy intelligent system for multi-objective supply chain network designs: an agent-based optimization state of the art," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1551-1579, October.
    2. Seyed Mohsen Mousavi & Ardeshir Bahreininejad & S. Nurmaya Musa & Farazila Yusof, 2017. "A modified particle swarm optimization for solving the integrated location and inventory control problems in a two-echelon supply chain network," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 191-206, January.
    3. Mogale, D.G. & Kumar, Mukesh & Kumar, Sri Krishna & Tiwari, Manoj Kumar, 2018. "Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 40-69.
    4. M. H. Alavidoost & Mosahar Tarimoradi & M. H. Fazel Zarandi, 2018. "Bi-objective mixed-integer nonlinear programming for multi-commodity tri-echelon supply chain networks," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 809-826, April.
    5. Reddy, K. Nageswara & Kumar, Akhilesh & Choudhary, Alok & Cheng, T. C. Edwin, 2022. "Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 735-752.
    6. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    7. Amalia I. Nikolopoulou & Panagiotis P. Repoussis & Christos D. Tarantilis & Emmanouil E. Zachariadis, 2019. "Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking," Operational Research, Springer, vol. 19(1), pages 1-38, March.
    8. Majid Eskandarpour & Pierre Dejax & Olivier Péton, 2019. "Multi-Directional Local Search for Sustainable Supply Chain Network Design," Post-Print hal-02407741, HAL.
    9. An, Kun & Ouyang, Yanfeng, 2016. "Robust grain supply chain design considering post-harvest loss and harvest timing equilibrium," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 110-128.
    10. Jingfeng Yuan & Wenying Ji & Jiyue Guo & Mirosław J. Skibniewski, 2019. "Simulation-based dynamic adjustments of prices and subsidies for transportation PPP projects based on stakeholders’ satisfaction," Transportation, Springer, vol. 46(6), pages 2309-2345, December.

    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. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    2. Kanokporn Kungwalsong & Abraham Mendoza & Vasanth Kamath & Subramanian Pazhani & Jose Antonio Marmolejo-Saucedo, 2022. "An application of interactive fuzzy optimization model for redesigning supply chain for resilience," Annals of Operations Research, Springer, vol. 315(2), pages 1803-1839, August.
    3. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    4. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    5. Walther, Grit & Schatka, Anne & Spengler, Thomas S., 2012. "Design of regional production networks for second generation synthetic bio-fuel – A case study in Northern Germany," European Journal of Operational Research, Elsevier, vol. 218(1), pages 280-292.
    6. Nickel, Stefan & Saldanha-da-Gama, Francisco & Ziegler, Hans-Peter, 2012. "A multi-stage stochastic supply network design problem with financial decisions and risk management," Omega, Elsevier, vol. 40(5), pages 511-524.
    7. Olivares-Benitez, Elias & Ríos-Mercado, Roger Z. & González-Velarde, José Luis, 2013. "A metaheuristic algorithm to solve the selection of transportation channels in supply chain design," International Journal of Production Economics, Elsevier, vol. 145(1), pages 161-172.
    8. Rezapour, Shabnam & Allen, Janet K. & Mistree, Farrokh, 2015. "Uncertainty propagation in a supply chain or supply network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 185-206.
    9. Chouinard, Marc & D'Amours, Sophie & Aït-Kadi, Daoud, 2008. "A stochastic programming approach for designing supply loops," International Journal of Production Economics, Elsevier, vol. 113(2), pages 657-677, June.
    10. Renato Matta, 2019. "Product costing in the strategic formation of a supply chain," Annals of Operations Research, Springer, vol. 272(1), pages 389-427, January.
    11. Tordecilla-Madera, Rafael & Polo, Andrés & Muñoz, Dairo & González-Rodríguez, Leonardo, 2017. "A robust design for a Colombian dairy cooperative's milk storage and refrigeration logistics system using binary programming," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 710-720.
    12. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2016. "The impact of operations anticipations on the quality of stochastic location-allocation models," Omega, Elsevier, vol. 62(C), pages 19-33.
    13. Ahmad Rezaee & Farzad Dehghanian & Behnam Fahimnia & Benita Beamon, 2017. "Green supply chain network design with stochastic demand and carbon price," Annals of Operations Research, Springer, vol. 250(2), pages 463-485, March.
    14. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    15. Toso, Eli Angela V. & Alem, Douglas, 2014. "Effective location models for sorting recyclables in public management," European Journal of Operational Research, Elsevier, vol. 234(3), pages 839-860.
    16. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    17. Li, Lei & Manier, Hervé & Manier, Marie-Ange, 2019. "Hydrogen supply chain network design: An optimization-oriented review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 342-360.
    18. Ma, N., 2014. "Optimal scope of supply chain network & operations design," Other publications TiSEM e6187708-b664-44bf-aef8-f, Tilburg University, School of Economics and Management.
    19. Mestre, Ana Maria & Oliveira, Mónica Duarte & Barbosa-Póvoa, Ana Paula, 2015. "Location–allocation approaches for hospital network planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 240(3), pages 791-806.
    20. Schweiger, Katharina & Sahamie, Ramin, 2013. "A hybrid Tabu Search approach for the design of a paper recycling network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 98-119.

    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:transb:v:60:y:2014:i:c:p:66-84. 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/548/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.