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A Hybrid Iterative Local Search Algorithm for The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations

机译:带时间窗和充电站的电动车队规模与混合动力车辆路径问题的混合迭代局部搜索算法

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As the cities around the world become larger, quality of life of the citizens is more and more threatened due to the traffic congestion, energy consumption, noise disturbance and carbon emissions because of of increasing transport. Electrical vehicles present an opportunity to reduce greenhouse gas emissions. But limited driving range and long recharging times are among the challenges that the research community has to face. This paper proposes an iterative local search algorithm coupled with a set partitioning model to solve The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations. Several types of electrical vehicles with varying driving range, capacity and fixed cost should service a set of customers within their time limits and during their tours each vehicle can be recharged in stations. We show the efficiency and the quality of our method by solving benchmark instances of the Heterogeneous Fleet Electric Vehicle Problems with Time Windows.
机译:随着世界各地城市规模的扩大,由于交通拥堵,交通拥堵,能源消耗,噪音干扰和碳排放,居民的生活质量受到越来越多的威胁。电动汽车为减少温室气体排放提供了机会。但是,有限的行驶里程和较长的充电时间是研究社区必须面对的挑战。本文提出了一种迭代的局部搜索算法,并结合了集合划分模型,以解决带时间窗和充电站的电动车队规模和混合车辆路径问题。行驶距离,容量和固定成本各不相同的几种类型的电动汽车应在其时限内为一组客户提供服务,并且在旅行期间,每辆电动汽车均可在车站充电。通过解决带有时间窗的异构机队电动汽车问题的基准实例,我们展示了我们方法的效率和质量。

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