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Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty

Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty

Michael C. Georgiadis, Pantelis Longinidis
Copyright: © 2011 |Pages: 36
ISBN13: 9781615206339|ISBN10: 1615206337|EISBN13: 9781615206346
DOI: 10.4018/978-1-61520-633-9.ch004
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MLA

Georgiadis, Michael C., and Pantelis Longinidis. "Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty." Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, edited by Ioannis Minis, et al., IGI Global, 2011, pp. 73-108. https://doi.org/10.4018/978-1-61520-633-9.ch004

APA

Georgiadis, M. C. & Longinidis, P. (2011). Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty. In I. Minis, V. Zeimpekis, G. Dounias, & N. Ampazis (Eds.), Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods (pp. 73-108). IGI Global. https://doi.org/10.4018/978-1-61520-633-9.ch004

Chicago

Georgiadis, Michael C., and Pantelis Longinidis. "Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty." In Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, edited by Ioannis Minis, et al., 73-108. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61520-633-9.ch004

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Abstract

This chapter considers a detailed mathematical formulation for the problem of designing supply chain networks comprising multiproduct production facilities with shared production resources, warehouses, distribution centers and customer zones and operating under time varying demand uncertainty. Uncertainty is captured in terms of a number of likely scenarios possible to materialize during the life time of the network. The problem is formulated as a mixed-integer linear programming problem and solved to global optimality using standard branch-and-bound techniques. A case study concerned with the establishment of Europe-wide supply chain is used to illustrate the applicability and efficiency of the proposed approach. The results obtained provide a good indication of the value of having a model that takes into account the complex interactions that exist in such networks and the effect of inventory levels to the design and operation.

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