可用的
计算机科学
任务(项目管理)
多目标优化
帕累托原理
电动汽车
数学优化
光学(聚焦)
质量(理念)
比例(比率)
运筹学
工程类
机器学习
系统工程
数学
功率(物理)
万维网
量子力学
认识论
哲学
物理
光学
作者
Marek Cuchý,Michal Jakob,Jan Mrkos
标识
DOI:10.1080/19427867.2024.2315359
摘要
Electric vehicle (EV) travel planning is a complex task that involves optimizing both the routes and the charging sessions for EVs. Existing algorithms rely on single-objective optimization, which limits their ability to consider EV users’ multiple, often conflicting objectives. In this paper, we introduce a new, genuinely multi-objective approach to EV travel planning, which can find Pareto sets containing multiple EV travel plans optimized simultaneously for multiple objectives. We focus on the bi-objective optimization for travel time and cost. To our knowledge, our algorithm is the first to perform such a genuine multi-objective optimization on realistically large country-scale problem instances involving 12,000 charging stations. We implemented our approach into a fully operational prototype application and extensively evaluated it on real-world data. Our results show that our approach can achieve practically usable planning times with only a minor loss of solution quality despite the very high computational complexity of the problem.
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