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MULTIOBJECTIVE MODEL PREDICTIVE CONTROL APPLIED TO A DIAL A-RIDE SYSTEM

机译:多目标模型预测控制在拨号自动驾驶系统中的应用

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A multiobjective model-based predictive control approach is presented for solving adial-a-ride problem. The dynamic objective function considers two dimensions: userand operator costs. As those two components are usually aimed at opposite goals, theproblem is formulated and solved through multiobjective model predictive control.When a new call asking for service is received, the method first solves a multiobjectiveoptimization problem, providing the Pareto optimal set. Note that from this set just onesolution has to be applied to the system. Then, the dispatcher participates in thedynamic routing decisions by expressing his/her preferences in a progressivelyinteractive way, seeking the best trade-off solution at each instant among the Paretooptimal set. The idea is to provide to the dispatcher a more transparent tool for thedecisions. Several criteria, emulating different dispatchers, are proposed in order tosystematize different ways to use the information provided by the dynamic optimalPareto front.An illustrative experiment of the new approach through simulation of the process ispresented to show the potential benefits in the operator cost and in the quality of serviceperceived by the users.
机译:提出了一种基于多目标模型的预测控制方法。 拨号问题。动态目标函数考虑两个维度:用户 和运营商成本。由于这两个组成部分通常是针对相反的目标,因此 通过多目标模型预测控制来制定和解决问题。 当收到新的服务呼叫时,该方法首先解决多目标问题 优化问题,提供帕累托最优集。请注意,在这个集合中,只有一个 解决方案必须应用于系统。然后,调度员参加 通过逐步表达自己的喜好来做出动态路由决策 互动方式,在帕累托中的每个瞬间寻求最佳的权衡解决方案 最佳设置。这个想法是为调度员提供一个更透明的工具, 决定。为了模拟不同的调度员,提出了一些标准。 系统化使用动态最优提供的信息的不同方式 帕累托战线。 通过模拟过程对新方法进行的说明性实验是 提出以显示在运营商成本和服务质量方面的潜在利益 被用户感知。

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