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Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry

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  • Liu, Songsong
  • Papageorgiou, Lazaros G.
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    Abstract

    The performance of a supply chain should usually be measured by multiple criteria. We address production, distribution and capacity planning of global supply chains considering cost, responsiveness and customer service level simultaneously. A multiobjective mixed-integer linear programming (MILP) approach is developed with total cost, total flow time and total lost sales as key objectives. Also, two strategies to expand the formulation plants’ capacities are considered in the model. The ε-constraint method and lexicographic minimax method are used as solution approaches to tackle the multiobjective problem. Finally, a numerical example is investigated to demonstrate the applicability of the proposed model and solution approaches.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 41 (2013)
    Issue (Month): 2 ()
    Pages: 369-382

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    Handle: RePEc:eee:jomega:v:41:y:2013:i:2:p:369-382

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    Related research

    Keywords: Multiobjective optimisation; Global supply chains; MILP; ε-constraint method; Lexicographic minimax method; Pareto-optimal solutions;

    References

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    3. Marchi, Ezio & Oviedo, Jorge A., 1992. "Lexicographic optimality in the multiple objective linear programming: The nucleolar solution," European Journal of Operational Research, Elsevier, vol. 57(3), pages 355-359, March.
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    16. Mula, Josefa & Peidro, David & Díaz-Madroñero, Manuel & Vicens, Eduardo, 2010. "Mathematical programming models for supply chain production and transport planning," European Journal of Operational Research, Elsevier, vol. 204(3), pages 377-390, August.
    17. Tsiakis, Panagiotis & Papageorgiou, Lazaros G., 2008. "Optimal production allocation and distribution supply chain networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 468-483, February.
    18. Wang, Lizhong & Fang, Liping & Hipel, Keith W., 2008. "Basin-wide cooperative water resources allocation," European Journal of Operational Research, Elsevier, vol. 190(3), pages 798-817, November.
    19. Pokharel, Shaligram, 2008. "A two objective model for decision making in a supply chain," International Journal of Production Economics, Elsevier, vol. 111(2), pages 378-388, February.
    20. Goetschalckx, Marc & Vidal, Carlos J. & Dogan, Koray, 2002. "Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms," European Journal of Operational Research, Elsevier, vol. 143(1), pages 1-18, November.
    21. Georgiadis, Michael C. & Tsiakis, Panagiotis & Longinidis, Pantelis & Sofioglou, Maria K., 2011. "Optimal design of supply chain networks under uncertain transient demand variations," Omega, Elsevier, vol. 39(3), pages 254-272, June.
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    Cited by:
    1. Longinidis, Pantelis & Georgiadis, Michael C., 2014. "Integration of sale and leaseback in the optimal design of supply chain networks," Omega, Elsevier, vol. 47(C), pages 73-89.
    2. Relvas, Susana & Boschetto Magatão, Suelen N. & Barbosa-Póvoa, Ana Paula F.D. & Neves, Flávio, 2013. "Integrated scheduling and inventory management of an oil products distribution system," Omega, Elsevier, vol. 41(6), pages 955-968.
    3. Sawik, Tadeusz, 2014. "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing," Omega, Elsevier, vol. 43(C), pages 83-95.

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