Territory Planning and Vehicle Dispatching with Driver Learning

Hongsheng Zhong (), Randolph W. Hall () and Maged Dessouky ()
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Hongsheng Zhong: United Parcel Service, 2311 York Road, Timonium, Maryland 21093
Randolph W. Hall: Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, California 90089
Maged Dessouky: Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, California 90089

Transportation Science, 2007, vol. 41, issue 1, 74-89

Abstract: This paper investigates the construction of routes for local delivery of packages. The primary objective of this research is to provide realistic models to optimize vehicle dispatching when customer locations and demands vary from day to day while maintaining driver familiarity with their service territories, hence dispatch consistency. The objective of increasing driver familiarity tends to make routes or service territories fixed. On the other hand, to serve varying demand it is advantageous to reassign vehicles/drivers and service territories each day. To balance the trade-offs between these two objectives, we developed the concepts of “cell,” “core area,” and “flex zone,” and created a two-stage vehicle routing model---strategic core area design and operational cell routing---and explicitly evaluated the effect of driver familiarity through the use of learning and forgetting curves.

Keywords: vehicle routing; driver learning; continuous approximations (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:41:y:2007:i:1:p:74-89

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