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Stochastic programming for flexible global supply chain planning

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Abstract

When ocean transportation is used, possible disruptions both at sea and on land should be taken into account in the planning process of the affected supply chain. In this paper, a framework to enable flexible global supply chain operational planning in stochastic environments is presented. In order to cope with unexpected events like natural or man-made disasters, flexible international long-distance transportation modes and postponement strategies are taken into account in our supply chain model. In order to balance supply chain costs and the flexibility of supply chains, a two-stage multi-scenario stochastic programming model is developed where the stochastic events are represented by corresponding scenarios. High quality solutions of all our problem instances are generated by using a Python based stochastic programming framework to solve the model. Finally, managerial insights related to flexible supply chain planning in stochastic environments are derived from our computational results.

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Notes

  1. Note that the abbreviation SC is used for both the singular and plural cases.

  2. This is a sample of a SC. Arrows represent the material/component/product flow directions. Dashed lines indicate vulnerable transportation links. Dashed boxes indicate vulnerable SC nodes.

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Acknowledgments

Yingjie Fan acknowledges financial support from the China Scholarship Council (CSC).

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Authors and Affiliations

  1. Institute of Information Systems, University of Hamburg, 20146, Hamburg, Germany

    Yingjie Fan, Frank Schwartz & Stefan Voß

  2. Graduate School of Management, University of California, Davis, CA, 95616, USA

    David L. Woodruff

  3. Department of Management Science, Xuzhou University of Technology, Xuzhou, 221008, Jiangsu, China

    Yingjie Fan

  4. Escuela de Ingenieriá Industrial, Pontificia Universidad Católica de Valparaíso, 2362807, Valparaiso, Chile

    Stefan Voß

Authors
  1. Yingjie Fan
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  2. Frank Schwartz
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  3. Stefan Voß
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  4. David L. Woodruff
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Correspondence to Yingjie Fan.

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Fan, Y., Schwartz, F., Voß, S. et al. Stochastic programming for flexible global supply chain planning. Flex Serv Manuf J 29, 601–633 (2017). https://doi.org/10.1007/s10696-016-9261-7

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  • DOI: https://doi.org/10.1007/s10696-016-9261-7

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