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Risk-cost optimization for procurement planning in multi-tier supply chain by Pareto Local Search with relaxed acceptance criterion

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  • Mori, Masakatsu
  • Kobayashi, Ryoji
  • Samejima, Masaki
  • Komoda, Norihisa

Abstract

We address a 2-objective optimization problem to minimize a retailer’s procurement cost and risk that is evaluated as recovery time of the retailer’s business after the procurement is suspended by a catastrophic event. In order to reduce the recovery time, the retailer needs to decentralize ordering to multiple suppliers and have contingency stock, which costs the retailer. In multi-tier supply chains, not only the retailer’s procurement plan but also their suppliers’ procurement plans affect the retailers’ risk and cost. Due to the huge combinations of their plans, it is difficult to find Pareto optimal solutions of the 2-objective optimization problem within a short space of time. We apply Pareto Local Search (PLS) based on heuristics to generate neighbors of a solution by changing suppliers’ plans in the closer tier to the retailer. The original PLS accepts the solutions that are nondominated neighbor solutions for the next search, but the acceptance criterion is too strict to find all Pareto optimal solutions. We relax the acceptance criterion in order to include dominated solutions whose Pareto rank is equal to or less than a threshold. The threshold is updated based on changes of Pareto rank during local searches.

Suggested Citation

  • Mori, Masakatsu & Kobayashi, Ryoji & Samejima, Masaki & Komoda, Norihisa, 2017. "Risk-cost optimization for procurement planning in multi-tier supply chain by Pareto Local Search with relaxed acceptance criterion," European Journal of Operational Research, Elsevier, vol. 261(1), pages 88-96.
  • Handle: RePEc:eee:ejores:v:261:y:2017:i:1:p:88-96
    DOI: 10.1016/j.ejor.2017.01.028
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    References listed on IDEAS

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    1. Dubois-Lacoste, Jérémie & López-Ibáñez, Manuel & Stützle, Thomas, 2015. "Anytime Pareto local search," European Journal of Operational Research, Elsevier, vol. 243(2), pages 369-385.
    2. Gaivoronski, Alexei & Sechi, Giovanni M. & Zuddas, Paola, 2012. "Cost/risk balanced management of scarce resources using stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 214-224.
    3. Christos Voudouris & Edward P.K. Tsang & Abdullah Alsheddy, 2010. "Guided Local Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 321-361, Springer.
    4. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    5. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    6. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    7. Ray, Pritee & Jenamani, Mamata, 2016. "Mean-variance analysis of sourcing decision under disruption risk," European Journal of Operational Research, Elsevier, vol. 250(2), pages 679-689.
    8. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    9. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    10. James R. Bradley, 2015. "An Evaluation of Capacity and Inventory Buffers as Mitigation for Catastrophic Supply Chain Disruptions," Springer Books, in: Andrew R. Thomas & Sebastian Vaduva (ed.), Global Supply Chain Security, edition 127, pages 99-116, Springer.
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    Cited by:

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