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Proximal Point Algorithms for Convex Multi-criteria Optimization with Applications to Supply Chain Risk Management

Author

Listed:
  • Shao-Jian Qu

    (Harbin Institute of Technology
    National University of Singapore)

  • Mark Goh

    (National University of Singapore
    National University of Singapore)

  • Robert Souza

    (National University of Singapore)

  • Tie-Nan Wang

    (Harbin Institute of Technology)

Abstract

We study a class of convex multi-criteria optimization problems with convex objective functions under linear constraints. We use a non-scalarization method—namely, two implementable proximal point algorithms—to obtain the Pareto optimum under multi-criteria optimization. We show that the algorithms are globally convergent. We apply the algorithms to a supply chain risk management problem under multi-criteria considerations.

Suggested Citation

  • Shao-Jian Qu & Mark Goh & Robert Souza & Tie-Nan Wang, 2014. "Proximal Point Algorithms for Convex Multi-criteria Optimization with Applications to Supply Chain Risk Management," Journal of Optimization Theory and Applications, Springer, vol. 163(3), pages 949-956, December.
  • Handle: RePEc:spr:joptap:v:163:y:2014:i:3:d:10.1007_s10957-014-0540-8
    DOI: 10.1007/s10957-014-0540-8
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    References listed on IDEAS

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    1. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    2. Villacorta, Kely D.V. & Oliveira, P. Roberto, 2011. "An interior proximal method in vector optimization," European Journal of Operational Research, Elsevier, vol. 214(3), pages 485-492, November.
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    Cited by:

    1. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    2. Qu, Shaojian & Ji, Ying & Jiang, Jianlin & Zhang, Qingpu, 2017. "Nonmonotone gradient methods for vector optimization with a portfolio optimization application," European Journal of Operational Research, Elsevier, vol. 263(2), pages 356-366.

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