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System-Centric Minimum-Time Paths for Battery-Powered Vehicles in Networks with Charging Nodes

机译:具有充电节点的网络中电池供电的电池供电车辆的以系统为中心的最小时间路径

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We study the routing problem for vehicle flows through a road network that includes both battery-powered Electric Vehicles (EVs) and Non-Electric Vehicles (NEVs). We seek to optimize a system-centric (as opposed to user-centric) objective aiming to minimize the total elapsed time for all vehicles to reach their destinations considering both traveling times and recharging times for EVs when the latter do not have adequate energy for the entire journey. Extending prior work where we considered only EVs entering the network, we formulate the problem by grouping all vehicles into a set of "subflows" and provide solutions based on both a Mixed Integer Non-Linear Programming (MINLP) approach and an alternative flow optimization problem. Since the problem size increases with the number of subflows, its proper selection is essential to render the problem manageable, thus reflecting a trade-off between proximity to optimality and computational effort needed to solve the problem. We propose a criterion and procedure leading to a "good" choice for the number of subflows.
机译:车辆流过包括电池供电的电动汽车(EV)和非电动车(NEVS)道路网络,我们研究的路由问题。我们寻求优化的系统为中心的(而不是用户为中心的)目标瞄准总减少运行时间为所有车辆到达目的地同时考虑旅行时间,对电动汽车的充电时间,当后者不具备足够的能量全程。扩展在这里我们只考虑进入网络的电动车,我们所有的车辆编组为一个集“子流程”的制定问题,并提供基于既有混合整数非线性规划(MINLP)的做法和替代流程优化问题的解决方案之前工作。由于与子流的数量问题规模的增大,它的正确选择是至关重要的渲染问题的管理,因此反映到最优性和解决问题所需要的计算工作量接近之间的权衡。我们提出的标准和程序,导致一个“好”的选择。子流的数量。

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