A dynamic driver management scheme for less-than-truckload carriers

Authors:
Alan Erera;Burak Karacık;Martin Savelsbergh
Affiliations:
The Supply Chain Logistics Institute, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205, USA;The Supply Chain Logistics Institute, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205, USA;The Supply Chain Logistics Institute, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205, USA
Venue:
Computers and Operations Research
Year:
2008

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Abstract

This paper describes a scheme for the dynamic management of linehaul drivers developed for a large US less-than-truckload (LTL) carrier. Virtually all scheduling problems faced by transportation service providers are complicated by time-constrained vehicle operators that can be renewed only after resting. LTL driver scheduling is further complicated by the fact that trucking moves, unlike passenger airline flights or train dispatches, are not pre-scheduled. The technology developed in this paper combines greedy search with enumeration of time-feasible driver duties, and is capable of generating in a matter of minutes cost-effective driver schedules covering 15,000-20,000 loads and satisfying a variety of real-life driver constraints. Computational results justify the algorithmic design choices made in the development of the scheme, and a comparison with real-world dispatch data indicates that the technology produces driver schedules of very high quality.