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dc.contributor.authorMcLean, Kyle
dc.contributor.authorOgbe, Emmanuel
dc.contributor.authorLi, Xiang
dc.date.accessioned2016-08-04T16:00:06Z
dc.date.available2016-08-04T16:00:06Z
dc.date.issued2015
dc.identifier.otherDOI: 10.1002/cjce.22173
dc.identifier.urihttp://hdl.handle.net/1974/14686
dc.descriptionThe authors would like to thank Dr. Defne Berkin for her help on defining and formulating the supply chain problem.en_US
dc.description.abstractThis paper is concerned with strategic optimization of a typical industrial chemical supply chain, which involves a material purchase and transportation network, several manufacturing plants with on-site material and product inventories, a product transportation network and several regional markets. In order to address large uncertainties in customer demands at the different regional markets, a novel robust scenario formulation, which has been developed by the authors recently, is tailored and applied for the strategic optimization. Case study results show that the robust scenario formulation works well for this real industrial supply chain system, and it outperforms the deterministic formulation and the classical scenario-based stochastic programming formulation by generating better expected economic performance and solutions that are guaranteed to be feasible for all uncertainty realizations. The robust scenario problem exhibits a decomposable structure that can be taken advantage of by Benders decomposition for efficient solution, so the application of Benders decomposition to the solution of the strategic optimization is also discussed. The case study results show that Benders decomposition can reduce the solution time by almost an order of magnitude when the number of scenarios in the problem is large.en_US
dc.description.sponsorshipDuPont-Queen’s Innovation Programme (DuQuIP).en_US
dc.language.isoenen_US
dc.publisherThe Canadian Journal of Chemical Engineeringen_US
dc.subjectSupply Chainen_US
dc.subjectUncertaintyen_US
dc.subjectStochastic Programmingen_US
dc.subjectRobust Scenario Formulationen_US
dc.subjectBenders Decompositionen_US
dc.titleNovel Formulation and Efficient Solution Strategy for Strategic Optimization of an Industrial Chemical Supply Chain Under Demand Uncertaintyen_US
dc.typeArticleen_US


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