电池(电)
公共交通
地铁列车时刻表
调度(生产过程)
可持续运输
充电站
计算机科学
运筹学
电
作业车间调度
旅行商问题
营业成本
遗传算法
汽车工程
电动汽车
工程类
数学优化
运输工程
功率(物理)
电气工程
运营管理
废物管理
机器学习
物理
操作系统
生物
持续性
量子力学
数学
生态学
算法
作者
Zhixin Wang,Feifeng Zheng,Sadeque Hamdan,Oualid Jouini
标识
DOI:10.1080/00207543.2024.2424973
摘要
Battery electric buses (BEBs) are recognised as sustainable modes of transportation. Because of its increasing range, efficient and convenient overnight charging has become crucial. The limited number of charging stations and variability in setup times require the optimisation of BEB charging schedules. This study proposes an optimal overnight centralised charging schedule that considers setup time and battery-degradation costs. We model this as a multi-travelling salesman problem with sojourn time to minimise operating costs, including electricity, setup time, and battery wear, while adhering to the bus-schedule constraints. We introduce a local search grouping genetic algorithm with a 2-opt operator local search to address the complexities of public-transport networks. Our extensive numerical analysis, grounded in real-world data, shows a 4.48% reduction in operating costs using our optimised strategy compared with current methods. Moreover, our charging-station allocation analysis provides insights for resource optimisation, advancing sustainable public transport, and charging strategies. This study contributes to the field of sustainable public transportation and charging optimisation.
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