期刊
TRANSPORTATION SCIENCE
卷 40, 期 2, 页码 211-225出版社
INFORMS
DOI: 10.1287/trsc.1050.0114
关键词
vehicle dispatching; real time; probabilistic knowledge; future events; parallel tabu search
An important, but seldom investigated, issue in the field of dynamic vehicle routing and dispatching is how to exploit information about future events to improve decision making. In this paper, we address this issue in a real-time setting with a strategy based on probabilistic knowledge about future request arrivals to better manage the fleet of vehicles. More precisely, the new strategy introduces dummy customers (representing forecasted requests) in vehicle routes to provide a good coverage of the territory. This strategy is assessed through computational experiments performed in a simulated environment.
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