Vendor selection

Vendor selection - Proeedlngr of the 2004 IEEE...

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Proeedlngr of the 2004 IEEE inbmatlonal Conhnnrn on RoboUu 6 Automation New means, IA April 2004 A Multiobjective Optimization Method for Strategic Sourcing and Inventory Replenishment Hongwei Ding, Lyks Benyoucef and Xiaolan Xie MACS1 Project INRIA (The French National Institutefor Research in Computer Science and Conlrol) ISGMP Bat. A, Ile du Soulcy, Met2 57000, FRANCE {ding & lyes.benyoucef & xie}@loria.fr Abshoef-A simulation-based multiobjective optimization method is proposed in this paper for joint decision-making on strategic sourcing and ioventory replenishment. More specifically, a multiobjective genetic algorithm is developed to determine the optimal supplier portfolio and inventory control parameters in order to reach best compromise of two conflicting criteria: costs and demand fill-rate. Discretwvent simulation is used to pronde faithful evaluation of these two criteria. Numerical results on a variant of a real case study are presented. Keywords-ultiobjecdve genetic olgorithm; simulofion; supplier selection; inventory replenishment; I. INTRODUCTION Supply chain design and management usually involve multiple conflicting optimization objectives, such as low costs, high quality, short leadtime and high demand fill-rate. Traditionally, the total cost of all supply chain activities is used as the key performance indicator (KPI) for supply chain optimization. However, in the current competition environment, it is not always desirable to reduce costs if this results in degraded customer service level. Trade-off between these conflicting performance indicators should he made by decision makers. Among numerous supply chain related problems, strategic sourcing and inventory replenishment are two research areas of significant practical impact. A large number of research works can he found in the literature respectively [1]-[8]. However, few of proposed techniques and methods deal with the two problems at the same time. One of the difficulties is the fact that strategic sourcing, principally supplier selection, is a decision at the strategic level, while inventory replenishment issues are rather at the operational level. Strategic decisions have long-term impacts on overall performances, which should be made in a comprehensive supply leadtime of suppliers have impacts on inventory replenishment parameters. Reversely, diversified inventory policies influence the requirements of supply leadtime. In such an industrial context, a multiobjective optimization method is indispensable in order to fmd best-compromised solutions, which makes joint decisions in a comprehensive manner. Genetic algorithm (CA) attracts more and more attentions for various optimization problems. CA is a parallel and evolutionaty search algorithm based on the Darwinian evolution theory. It is used to search large, nonlinear solution space where expert knowledge is lacking or difficult to encode [lo]. In addition, it requires no gradient information, evolves from one population to another and produces multiple optima
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This note was uploaded on 06/16/2010 for the course MS&E 369 taught by Professor Blakejohnson during the Spring '08 term at Stanford.

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Vendor selection - Proeedlngr of the 2004 IEEE...

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