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Route optimization of an electric garbage truck fleet for sustainable environmental and energy management

机译:用于可持续环境和能源管理电动垃圾车舰队的路线优化

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The waste collection process is an issue where numerous studies have already been conducted in the existing literature especially based on finding the optimal routes for the garbage trucks assigned in this service process. In this manner, A Mixed-Integer Linear Programming (MILP) based route optimization model has been conducted as the first attempt for waste collection-oriented electric garbage trucks routing process in this study. Even different studies exist in the literature for the route optimization of conventional fuels-based garbage trucks as mentioned above, no studies devote to considering the electric garbage trucks to the best of our knowledge. Besides, it is not easy to reach the detailed garbage collection area information in the literature. In this manner, data have been obtained by real field measurements in a region within the service area of Bakirkoy Municipality, Istanbul, Turkey. A unit energy consumption value that can be considered as a reference in the future has also been obtained using real data. Besides, real road information data have been integrated to the data used as input while assessing the optimization approach and the system analyses have been conducted in a more realistic concept. The proposed concept has led to an increased reality of nearly 38% for the analysis of the results under conditions closer to real-time, and a decrement of nearly 32% has been obtained. It is expected that this study may lead a conceptual input to an enhanced and greener waste collection process. (C) 2019 Elsevier Ltd. All rights reserved.
机译:废物收集过程是现有文献中已经在现有文献中进行了许多研究的问题,特别是根据找到在此服务过程中分配的垃圾车的最佳路线。以这种方式,已经进行了混合整数线性编程(MILP)的路线优化模型作为在本研究中的废物收集的电动垃圾车路由过程的第一次尝试。如上所述,对于传统燃料的垃圾车的路线优化的文献中存在甚至存在的不同研究,没有研究旨在考虑电动垃圾车,以便我们的知识。此外,在文献中达到详细的垃圾收集区信息并不容易。以这种方式,通过土耳其伊斯坦布尔的伊斯坦布尔的服务区内的一个区域中的真实场测量获得了数据。可以使用真实数据获得可以被视为作为参考的单位能量消耗值。此外,真实的道路信息数据已经集成到用作输入的数据,同时评估优化方法,并以更现实的概念进行系统分析。拟议的概念导致了近38%的现实,用于在更接近实时的条件下分析结果,并且已经获得了近32%的减少。预计本研究可能会导致增强和更环保的废物收集过程的概念性输入。 (c)2019 Elsevier Ltd.保留所有权利。

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