The Robust Optimization in Centralized Supply Chain

Li Chenlu

doi:doi:10.11648/j.sjbm.20160402.16

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The Robust Optimization in Centralized Supply Chain

Li Chenlu

Published in Science Journal of Business and Management (Volume 4, Issue 2)

Received: 4 May 2016 Published: 5 May 2016

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Abstract

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.

Published in	Science Journal of Business and Management (Volume 4, Issue 2)
DOI	10.11648/j.sjbm.20160402.16
Page(s)	61-66
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Supply Chain, Robust Optimization, Demand Forecasting Uncertainty, Fast Fourier Transform Approach

References

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APA Style

Li Chenlu. (2016). The Robust Optimization in Centralized Supply Chain. Science Journal of Business and Management, 4(2), 61-66. https://doi.org/10.11648/j.sjbm.20160402.16

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ACS Style

Li Chenlu. The Robust Optimization in Centralized Supply Chain. Sci. J. Bus. Manag. 2016, 4(2), 61-66. doi: 10.11648/j.sjbm.20160402.16

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AMA Style

Li Chenlu. The Robust Optimization in Centralized Supply Chain. Sci J Bus Manag. 2016;4(2):61-66. doi: 10.11648/j.sjbm.20160402.16

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@article{10.11648/j.sjbm.20160402.16,
  author = {Li Chenlu},
  title = {The Robust Optimization in Centralized Supply Chain},
  journal = {Science Journal of Business and Management},
  volume = {4},
  number = {2},
  pages = {61-66},
  doi = {10.11648/j.sjbm.20160402.16},
  url = {https://doi.org/10.11648/j.sjbm.20160402.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20160402.16},
  abstract = {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.},
 year = {2016}
}

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TY  - JOUR
T1  - The Robust Optimization in Centralized Supply Chain
AU  - Li Chenlu
Y1  - 2016/05/05
PY  - 2016
N1  - https://doi.org/10.11648/j.sjbm.20160402.16
DO  - 10.11648/j.sjbm.20160402.16
T2  - Science Journal of Business and Management
JF  - Science Journal of Business and Management
JO  - Science Journal of Business and Management
SP  - 61
EP  - 66
PB  - Science Publishing Group
SN  - 2331-0634
UR  - https://doi.org/10.11648/j.sjbm.20160402.16
AB  - 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.
VL  - 4
IS  - 2
ER  -

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Author Information

Li Chenlu

School of Management, Shanghai University, Shanghai, China

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Plain Text BibTeX RIS

APA Style

Li Chenlu. (2016). The Robust Optimization in Centralized Supply Chain. Science Journal of Business and Management, 4(2), 61-66. https://doi.org/10.11648/j.sjbm.20160402.16

Copy | Download

ACS Style

Li Chenlu. The Robust Optimization in Centralized Supply Chain. Sci. J. Bus. Manag. 2016, 4(2), 61-66. doi: 10.11648/j.sjbm.20160402.16

Copy | Download

AMA Style

Li Chenlu. The Robust Optimization in Centralized Supply Chain. Sci J Bus Manag. 2016;4(2):61-66. doi: 10.11648/j.sjbm.20160402.16

Copy | Download

@article{10.11648/j.sjbm.20160402.16,
  author = {Li Chenlu},
  title = {The Robust Optimization in Centralized Supply Chain},
  journal = {Science Journal of Business and Management},
  volume = {4},
  number = {2},
  pages = {61-66},
  doi = {10.11648/j.sjbm.20160402.16},
  url = {https://doi.org/10.11648/j.sjbm.20160402.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20160402.16},
  abstract = {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.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - The Robust Optimization in Centralized Supply Chain
AU  - Li Chenlu
Y1  - 2016/05/05
PY  - 2016
N1  - https://doi.org/10.11648/j.sjbm.20160402.16
DO  - 10.11648/j.sjbm.20160402.16
T2  - Science Journal of Business and Management
JF  - Science Journal of Business and Management
JO  - Science Journal of Business and Management
SP  - 61
EP  - 66
PB  - Science Publishing Group
SN  - 2331-0634
UR  - https://doi.org/10.11648/j.sjbm.20160402.16
AB  - 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.
VL  - 4
IS  - 2
ER  -

Copy | Download