Exploiting knowledge about future demands for real-time vehicle dispatching

被引:152
作者
Ichoua, Soumia [1 ]
Gendreau, Michel
Potvin, Jean-Yves
机构
[1] Univ Laval, Dept Operat & Syst Decis, Quebec City, PQ G1K 7P4, Canada
[2] Univ Laval, Ctr Rech Technol, Org Reseau, Quebec City, PQ G1K 7P4, Canada
[3] Univ Montreal, Dept Informat & Rech Operat, Montreal, PQ H3C 3J7, Canada
[4] Univ Montreal, Ctr Rech Transports, Montreal, PQ H3C 3J7, Canada
关键词
vehicle dispatching; real time; probabilistic knowledge; future events; parallel tabu search;
D O I
10.1287/trsc.1050.0114
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:211 / 225
页数:15
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