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Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition

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  • Keyvanshokooh, Esmaeil
  • Ryan, Sarah M.
  • Kabir, Elnaz

Abstract

Environmental, social and economic concerns motivate the operation of closed-loop supply chain networks (CLSCN) in many industries. We propose a novel profit maximization model for CLSCN design as a mixed-integer linear program in which there is flexibility in covering the proportions of demand satisfied and returns collected based on the firm's policies. Our major contribution is to develop a novel hybrid robust-stochastic programming (HRSP) approach to simultaneously model two different types of uncertainties by including stochastic scenarios for transportation costs and polyhedral uncertainty sets for demands and returns. Transportation cost scenarios are generated using a Latin Hypercube Sampling method and scenario reduction is applied to consolidate them. An accelerated stochastic Benders decomposition algorithm is proposed for solving this model. To speed up the convergence of this algorithm, valid inequalities are introduced to improve the lower bound quality, and also a Pareto-optimal cut generation scheme is used to strengthen the Benders optimality cuts. Numerical studies are performed to verify our mathematical formulation and also demonstrate the benefits of the HRSP approach. The performance improvements achieved by the valid inequalities and Pareto-optimal cuts are demonstrated in randomly generated instances.

Suggested Citation

  • Keyvanshokooh, Esmaeil & Ryan, Sarah M. & Kabir, Elnaz, 2016. "Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition," European Journal of Operational Research, Elsevier, vol. 249(1), pages 76-92.
  • Handle: RePEc:eee:ejores:v:249:y:2016:i:1:p:76-92
    DOI: 10.1016/j.ejor.2015.08.028
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    1. Gülpınar, Nalan & Pachamanova, Dessislava & Çanakoğlu, Ethem, 2013. "Robust strategies for facility location under uncertainty," European Journal of Operational Research, Elsevier, vol. 225(1), pages 21-35.
    2. Schütz, Peter & Tomasgard, Asgeir & Ahmed, Shabbir, 2009. "Supply chain design under uncertainty using sample average approximation and dual decomposition," European Journal of Operational Research, Elsevier, vol. 199(2), pages 409-419, December.
    3. Dekker, Rommert & Bloemhof, Jacqueline & Mallidis, Ioannis, 2012. "Operations Research for green logistics – An overview of aspects, issues, contributions and challenges," European Journal of Operational Research, Elsevier, vol. 219(3), pages 671-679.
    4. Niknejad, A. & Petrovic, D., 2014. "Optimisation of integrated reverse logistics networks with different product recovery routes," European Journal of Operational Research, Elsevier, vol. 238(1), pages 143-154.
    5. Devika, K. & Jafarian, A. & Nourbakhsh, V., 2014. "Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques," European Journal of Operational Research, Elsevier, vol. 235(3), pages 594-615.
    6. Shi, Wen & Liu, Zhixue & Shang, Jennifer & Cui, Yujia, 2013. "Multi-criteria robust design of a JIT-based cross-docking distribution center for an auto parts supply chain," European Journal of Operational Research, Elsevier, vol. 229(3), pages 695-706.
    7. Aras, Necati & Aksen, Deniz & Gönül Tanugur, Ayse, 2008. "Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1223-1240, December.
    8. Faccio, M. & Persona, A. & Sgarbossa, F. & Zanin, G., 2014. "Sustainable SC through the complete reprocessing of end-of-life products by manufacturers: A traditional versus social responsibility company perspective," European Journal of Operational Research, Elsevier, vol. 233(2), pages 359-373.
    9. Cruz-Rivera, Reynaldo & Ertel, Jürgen, 2009. "Reverse logistics network design for the collection of End-of-Life Vehicles in Mexico," European Journal of Operational Research, Elsevier, vol. 196(3), pages 930-939, August.
    10. Klibi, Walid & Martel, Alain, 2012. "Scenario-based Supply Chain Network risk modeling," European Journal of Operational Research, Elsevier, vol. 223(3), pages 644-658.
    11. Salema, Maria Isabel Gomes & Barbosa-Povoa, Ana Paula & Novais, Augusto Q., 2007. "An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1063-1077, June.
    12. Soleimani, Hamed & Govindan, Kannan, 2014. "Reverse logistics network design and planning utilizing conditional value at risk," European Journal of Operational Research, Elsevier, vol. 237(2), pages 487-497.
    13. Cardoso, Sónia R. & Barbosa-Póvoa, Ana Paula F.D. & Relvas, Susana, 2013. "Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 226(3), pages 436-451.
    14. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2010. "The design of robust value-creating supply chain networks: A critical review," European Journal of Operational Research, Elsevier, vol. 203(2), pages 283-293, June.
    15. De Giovanni, Pietro & Zaccour, Georges, 2014. "A two-period game of a closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 232(1), pages 22-40.
    16. Brandenburg, Marcus & Govindan, Kannan & Sarkis, Joseph & Seuring, Stefan, 2014. "Quantitative models for sustainable supply chain management: Developments and directions," European Journal of Operational Research, Elsevier, vol. 233(2), pages 299-312.
    17. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    18. Dale McDaniel & Mike Devine, 1977. "A Modified Benders' Partitioning Algorithm for Mixed Integer Programming," Management Science, INFORMS, vol. 24(3), pages 312-319, November.
    19. de Sá, Elisangela Martins & de Camargo, Ricardo Saraiva & de Miranda, Gilberto, 2013. "An improved Benders decomposition algorithm for the tree of hubs location problem," European Journal of Operational Research, Elsevier, vol. 226(2), pages 185-202.
    20. 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.
    21. 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.
    22. 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.
    23. Alumur, Sibel A. & Nickel, Stefan & Saldanha-da-Gama, Francisco & Verter, Vedat, 2012. "Multi-period reverse logistics network design," European Journal of Operational Research, Elsevier, vol. 220(1), pages 67-78.
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