Evaluating city logistics measures using a multi-agent model
Evaluating city logistics measures using a multi-agent model
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DOI：
10.1016/j.sbspro.2010.04.014
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
D. Tamagawa;E. Taniguchi;Tadashi Yamada
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文献类型：
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作者：
D. Tamagawa;E. Taniguchi;Tadashi Yamada
本文提出了一种评估城市物流措施的方法，考虑到与城市货运相关的多个利益相关者的行为，使用多代理模型。该模型由学习模型和带时间窗预测的车辆路径与调度问题模型（VRP-TW-F）组成。我们使用了Q学习的方法，强化学习的技术，在构建学习模型。我们实现了一个测试道路网络代表一个城市地区的模型。结果表明，直接在环境受损地区实施卡车禁令和在城市高速公路网络中完全折扣高速公路通行费对环境有很大的影响，并为所有利益相关者带来可接受的环境。
This paper presents a methodology for evaluating city logistics measures considering the behaviour of several stakeholders associated with urban freight transport using a multi-agent model. The model constructed consists of a learning model and a model for vehicle routing and scheduling problem with time window-forecasted (VRP-TW-F). We used a method of Q-learning, a technique of reinforcement learning, in constructing a learning model. We implemented the model on a test road network representing an urban area. The results indicate that implementing a truck ban directly to environmentally damaged areas and discounting motorway tolls entirely in the urban motorway network together has large environmental effects, and leads to an acceptable environment for all stakeholders.