Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/42287
標題: A possibilistic decision model for new product supply chain design
作者: Wang, J.T.
王瑞德
Shu, Y.F.
關鍵字: supply chain management
fuzzy sets
new product development
genetic
algorithms
possibility theory
engineering design
fuzzy
management
optimization
selection
systems
期刊/報告no:: European Journal of Operational Research, Volume 177, Issue 2, Page(s) 1044-1061.
摘要: This paper models supply chain (SC) uncertainties by fuzzy sets and develops a possibilistic SC configuration model for new products with unreliable or unavailable SC statistical data. The supply chain is modeled as a network of stages. Each stage may have one or more options characterized by the cost and lead-time required to fulfill required functions and may hold safety stock to prevent an inventory shortage. The objective is to determine the option and inventory policy for each stage to minimize the total SC cost and maximize the possibility of fulfilling the target service level. A fuzzy SC model is developed to evaluate the performance of the entire SC and a genetic algorithm approach is applied to determine near-optimal solutions. The results obtained show that the proposed approach allows decision makers to perform trade-off analysis among customer service levels, product cost, and inventory investment depending on their risk attitude. It also provides an alternative tool to evaluate and improve SC configuration decisions in an uncertain SC environment. (c) 2006 Elsevier B.V. All rights reserved.
URI: http://hdl.handle.net/11455/42287
ISSN: 0377-2217
文章連結: http://dx.doi.org/10.1016/j.ejor.2005.12.032
Appears in Collections:科技管理研究所

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