《工程管理前沿（英文）》
>> 2017年
第4卷
第3期
doi:
10.15302/J-FEM-2017032
RESEARCH ARTICLE
A case study on sample average approximation method for stochastic supply chain network design problem
Department of Industrial Systems Engineering & Management, National University of Singapore, Singapore 117576, Singapore
录用日期：
2017-09-28
发布日期：
2017-10-30
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摘要
This study aims to solve a typical long-term strategic decision problem on supply chain network design with consideration to uncertain demands. Existing methods for these problems are either deterministic or limited in scale. We analyze the impact of uncertainty on demand based on actual large data from industrial companies. Deterministic equivalent model with nonanticipativity constraints, branch-and-fix coordination, sample average approximation (SAA) with Bayesian bootstrap, and Latin hypercube sampling were adopted to analyze stochastic demands. A computational study of supply chain network with front-ends in Europe and back-ends in Asia is presented to highlight the importance of stochastic factors in these problems and the efficiency of our proposed solution approach.
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