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Indexed by:期刊论文

Date of Publication:2011-12-16

Journal:EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Included Journals:SCIE、SSCI、Scopus

Volume:215

Issue:3

Page Number:590-603

ISSN No.:0377-2217

Key Words:Supply chain management; Uncertainty modeling; Production planning; Fuzzy sets; Stochastic chance-constrained programming; Evolutionary computations

Abstract:This research is motivated by an automobile manufacturing supply chain network. It involves a multi-echelon production system with material supply, component fabrication, manufacturing, and final product distribution activities. We address the production planning issue by considering bill of materials and the trade-offs between inventories, production costs and customer service level. Due to its complexity, an integrated solution framework which combines scatter evolutionary algorithm, fuzzy programming and stochastic chance-constrained programming are combined to jointly take up the issue. We conduct a computational study to evaluate the model. Numerical results using the proposed algorithm confirm the advantage of the integrated planning approach. Compared with other solution methodologies, the supply chain profits from the proposed approach consistently outperform, in some cases up to 13% better. The impacts of uncertainty in demand, material price, and other parameters on the performance of the supply chain are studied through sensitivity analysis. We found the proposed model is effective in developing robust production plans under various market conditions. (C) 2011 Elsevier B.V. All rights reserved.