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The effect of multi-scenario policies on empty container repositioning

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  • Di Francesco, Massimo
  • Crainic, Teodor Gabriel
  • Zuddas, Paola
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    Abstract

    This paper addresses a container maritime-repositioning problem where several parameters are uncertain and historical data are useless for decision-making processes. To address this problem, we propose a time-extended multi-scenario optimization model in which scenarios can be generated taking into account shipping company opinions. We then show that multi-scenario policies put shipping companies in the position of satisfying empty-container demands for different values that may be taken by uncertain parameters.

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    File URL: http://www.sciencedirect.com/science/article/pii/S1366554509000325
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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 45 (2009)
    Issue (Month): 5 (September)
    Pages: 758-770

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    Handle: RePEc:eee:transe:v:45:y:2009:i:5:p:758-770

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    Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description

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    Related research

    Keywords: Empty container repositioning Mathematical modeling Time-extended optimization models Multicommodity flow problems Optimization under uncertainty;

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    Cited by:
    1. Mittal, Neha & Boile, Maria & Baveja, Alok & Theofanis, Sotiris, 2013. "Determining optimal inland-empty-container depot locations under stochastic demand," Research in Transportation Economics, Elsevier, vol. 42(1), pages 50-60.
    2. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship fleet deployment with container transshipment operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 470-484.
    3. Long, Yin & Lee, Loo Hay & Chew, Ek Peng, 2012. "The sample average approximation method for empty container repositioning with uncertainties," European Journal of Operational Research, Elsevier, vol. 222(1), pages 65-75.
    4. Gaivoronski, Alexei & Sechi, Giovanni M. & Zuddas, Paola, 2012. "Cost/risk balanced management of scarce resources using stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 214-224.

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