动态随机VRPTW的多阶段随机规划方法
A Multistage Stochastic Programming Approach to the Dynamic and Stochastic VRPTW - Extended version
摘要：
我们考虑一个动态车辆路径问题的时间窗口和随机客户（DS-VRPTW），这样客户可能会要求服务的车辆已经开始他们的旅行。为了解决这个问题，我们的目标是提供一个决策规则，选择，在每个时间步，根据已知的请求和概率知识的请求可能性执行的下一个动作。我们引入了一个新的决策规则，称为全球随机评估（GSA）规则的DS-VRPTW，我们比较它与现有的决策规则，如MSA。特别是，我们表明，GSA完全集成nonanticipativity约束，使它导致更好的决策，在我们的随机环境。我们描述了一种新的启发式方法，有效地近似我们的GSA规则。我们引入了新的等待策略。动态和随机基准，其中包括不同程度的动态的实例上的实验表明，我们的方法不仅是具有竞争力的国家的最先进的方法，而且还能够计算有意义的离线解决方案，完全动态的问题，绝对没有先验的客户请求提供。
英文摘要：
We consider a dynamic vehicle routing problem with time windows and stochastic customers (DS-VRPTW), such that customers may request for services as vehicles have already started their tours. To solve this problem, the goal is to provide a decision rule for choosing, at each time step, the next action to perform in light of known requests and probabilistic knowledge on requests likelihood. We introduce a new decision rule, called Global Stochastic Assessment (GSA) rule for the DS-VRPTW, and we compare it with existing decision rules, such as MSA. In particular, we show that GSA fully integrates nonanticipativity constraints so that it leads to better decisions in our stochastic context. We describe a new heuristic approach for efficiently approximating our GSA rule. We introduce a new waiting strategy. Experiments on dynamic and stochastic benchmarks, which include instances of different degrees of dynamism, show that not only our approach is competitive with state-of-the-art methods, but also enables to compute meaningful offline solutions to fully dynamic problems where absolutely no a priori customer request is provided.
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