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The performance of route modification and demand stabilization strategies in stochastic vehicle routing

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  • Haughton, Michael A.

Abstract

A key concern in managing vehicle routing operations under stochastic demands is whether, on the basis of travel distance, route modification yields materially greater logistical efficiency than fixed routes. This research uses statistical calibration as the primary technique to develop a robust and tractable model for estimating this difference in logistical efficiency. Based on features such as the models predictive accuracy and generalizability, it constitutes a substantive improvement over existing models. The present study also expands the range of predictive models relevant to vehicle routing under stochastic demands with models to estimate the transportation and inventory effects of persuading customers to stabilize their ordering patterns.

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  • Haughton, Michael A., 1998. "The performance of route modification and demand stabilization strategies in stochastic vehicle routing," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 551-566, November.
    • Handle: RePEc:eee:transb:v:32:y:1998:i:8:p:551-566
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    References listed on IDEAS

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    Cited by:

    1. Spliet, R. & Gabor, A.F. & Dekker, R., 2009. "The Vehicle Rescheduling Problem," Econometric Institute Research Papers EI 2009-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Jinil Han & Chungmok Lee & Sungsoo Park, 2014. "A Robust Scenario Approach for the Vehicle Routing Problem with Uncertain Travel Times," Transportation Science, INFORMS, vol. 48(3), pages 373-390, August.
    3. Michel Beuthe, 2011. "Economics of Transport Logistics," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 11, Edward Elgar Publishing.
    4. Hongsheng Zhong & Randolph W. Hall & Maged Dessouky, 2007. "Territory Planning and Vehicle Dispatching with Driver Learning," Transportation Science, INFORMS, vol. 41(1), pages 74-89, February.

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