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Efficient Production-Distribution System Design

Author

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  • Samir Elhedhli

    (Department of Management Sciences, University of Waterloo, 200 University West, Waterloo, Ontario N2L 3G1, Canada)

  • Jean-Louis Goffin

    (Faculty of Management, McGill University, 1001 Sherbrooke West, Montreal, Quebec H3A 1G5, Canada)

Abstract

The production-distribution system design is an integral part of the general supply chain design. This paper proposes a novel solution methodology for this problem that is based on Lagrangean relaxation, interior-point methods, and branch and bound. Unlike classical approaches, Lagrangean relaxation is applied in a two-level hierarchy, branch and bound is based on a Lagrangean lower bound and column generation (branch and price), while interior-point methods are used within a cutting-plane context (analytic centre cutting-plane method---ACCPM). Numerical results demonstrate that the two-level approach outperforms the classical approach and provides a very sharp lower bound that is the (proven) optimal in most cases.

Suggested Citation

  • Samir Elhedhli & Jean-Louis Goffin, 2005. "Efficient Production-Distribution System Design," Management Science, INFORMS, vol. 51(7), pages 1151-1164, July.
  • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:7:p:1151-1164
    DOI: 10.1287/mnsc.1050.0392
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    References listed on IDEAS

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    2. Wu, Tao & Xiao, Fan & Zhang, Canrong & Zhang, Defu & Liang, Zhe, 2019. "Regression and extrapolation guided optimization for production–distribution with ship–buy–exchange options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 15-37.
    3. Edirisinghe, Chanaka & Jeong, Jaehwan, 2019. "Indefinite multi-constrained separable quadratic optimization: Large-scale efficient solution," European Journal of Operational Research, Elsevier, vol. 278(1), pages 49-63.
    4. Sheu, Jiuh Biing & Kundu, Tanmoy, 2018. "Forecasting time-varying logistics distribution flows in the One Belt-One Road strategic context," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 117(C), pages 5-22.
    5. Tilk, Christian & Drexl, Michael & Irnich, Stefan, 2019. "Nested branch-and-price-and-cut for vehicle routing problems with multiple resource interdependencies," European Journal of Operational Research, Elsevier, vol. 276(2), pages 549-565.
    6. Morteza Abbasi & Reza Hosnavi & Mehrdad Mohammadi, 2013. "Designing a Fuzzy Strategic Integrated Multiechelon Agile Supply Chain Network," Journal of Optimization, Hindawi, vol. 2013, pages 1-16, June.
    7. Navneet Vidyarthi & Emre Çelebi & Samir Elhedhli & Elizabeth Jewkes, 2007. "Integrated Production-Inventory-Distribution System Design with Risk Pooling: Model Formulation and Heuristic Solution," Transportation Science, INFORMS, vol. 41(3), pages 392-408, August.
    8. David Bergman, 2019. "An Exact Algorithm for the Quadratic Multiknapsack Problem with an Application to Event Seating," INFORMS Journal on Computing, INFORMS, vol. 31(3), pages 477-492, July.
    9. F. Jolai & J. Razmi & N. Rostami, 2011. "A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem," 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. 19(4), pages 547-569, December.
    10. 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.
    11. Fleszar, Krzysztof, 2022. "A branch-and-bound algorithm for the quadratic multiple knapsack problem," European Journal of Operational Research, Elsevier, vol. 298(1), pages 89-98.
    12. Christian Tilk & Michael Drexl & Stefan Irnich, 2018. "Nested Branch-and-Price-and-Cut for Vehicle Routing Problems with Multiple Resource Interdependencies," Working Papers 1801, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    13. Pan, Feng & Nagi, Rakesh, 2013. "Multi-echelon supply chain network design in agile manufacturing," Omega, Elsevier, vol. 41(6), pages 969-983.
    14. Yuji Nakagawa & Ross J. W. James & César Rego & Chanaka Edirisinghe, 2014. "Entropy-Based Optimization of Nonlinear Separable Discrete Decision Models," Management Science, INFORMS, vol. 60(3), pages 695-707, March.
    15. Mourgaya, M. & Vanderbeck, F., 2007. "Column generation based heuristic for tactical planning in multi-period vehicle routing," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1028-1041, December.
    16. Cheng, Bayi & Leung, Joseph Y.-T. & Li, Kai & Yang, Shanlin, 2019. "Integrated optimization of material supplying, manufacturing, and product distribution: Models and fast algorithms," European Journal of Operational Research, Elsevier, vol. 277(1), pages 100-111.
    17. Caris, An & Limbourg, Sabine & Macharis, Cathy & van Lier, Tom & Cools, Mario, 2014. "Integration of inland waterway transport in the intermodal supply chain: a taxonomy of research challenges," Journal of Transport Geography, Elsevier, vol. 41(C), pages 126-136.

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