Abstract
There has been considerable recent interest in the dynamic vehicle routing problem, but the complexities of this problem class have generally restricted research to myopic models. In this paper, we address the simpler dynamic assignment problem, where a resource (container, vehicle, or driver) can serve only one task at a time. We propose a very general class of dynamic assignment models, and propose an adaptive, nonmyopic algorithm that involves iteratively solving sequences of assignment problems no larger than what would be required of a myopic model. We consider problems where the attribute space of future resources and tasks is small enough to be enumerated, and propose a hierarchical aggregation strategy for problems where the attribute spaces are too large to be enumerated. Finally, we use the formulation to also test the value of advance information, which offers a more realistic estimate over studies that use purely myopic models.
Original language | English (US) |
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Pages (from-to) | 399-419 |
Number of pages | 21 |
Journal | Transportation Science |
Volume | 38 |
Issue number | 4 |
DOIs | |
State | Published - Nov 2004 |
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Transportation
Keywords
- Approximate dynamic programming
- Dynamic assignment
- Dynamic vehicle routing