Scenario-based planning for partially dynamic vehicle routing with stochastic customers
成果类型：
Article
署名作者：
Bent, RW; Van Hentenryck, P
署名单位：
Brown University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1040.0124
发表日期：
2004
页码：
977-987
关键词：
摘要：
The multiple vehicle routing problem with time windows (VRPTW) is a hard and extensively studied combinatorial optimization problem. This paper considers a dynamic VRPTW with stochastic customers, where the goal is to maximize the number of serviced customers. It presents a multiple scenario approach (MSA) that continuously generates routing plans for scenarios including known and future requests. Decisions during execution use a distinguished plan chosen, at each decision, by a consensus function. The approach was evaluated on vehicle routing problems adapted from the Solomon benchmarks with a degree of dynamism varying between 30% and 80%. They indicate that MSA exhibits dramatic improvements over approaches not exploiting stochastic information, that the use of consensus function improves the quality of the solutions significantly, and that the benefits of MSA increase with the (effective) degree of dynamism.