The Robust Optimization in Centralized Supply Chain
Science Journal of Business and Management
Volume 4, Issue 2, April 2016, Pages: 61-66
Received: May 4, 2016; Published: May 5, 2016
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Li Chenlu, School of Management, Shanghai University, Shanghai, China
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Considering the inaccurate demand forecasting in supply chain, we introduce robust optimization to reduce uncertainty. The method is mainly to modify the probability distribution of the demand, in order to obtain a more accurate demand. A classical model and a corresponding robust model are established in the context of a fixed number of products offered by the supplier. As to calculation, we also propose the fast Fourier transform approach which greatly reduces the amount of computation. Finally, the process of robust optimization and improved algorithm are interpreted by numerical examples. The results show that the expected revenue of the robust model is lower. Because the method is conservative and robust.
Supply Chain, Robust Optimization, Demand Forecasting Uncertainty, Fast Fourier Transform Approach
To cite this article
Li Chenlu, The Robust Optimization in Centralized Supply Chain, Science Journal of Business and Management. Vol. 4, No. 2, 2016, pp. 61-66. doi: 10.11648/j.sjbm.20160402.16
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