A Time-Dependent Electric Vehicle Routing Problem With Congestion Tolls
| Autor: | Junwei Wang, Ruiyou Zhang, Jingmei Guo |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Mathematical optimization
business.product_category biology Computer science Heuristic (computer science) Strategy and Management Open problem 05 social sciences Scheduling (computing) Traffic congestion Toll 0502 economics and business Electric vehicle Benchmark (computing) biology.protein Electrical and Electronic Engineering Routing (electronic design automation) business 050203 business & management |
| Zdroj: | IEEE Transactions on Engineering Management. 69:861-873 |
| ISSN: | 1558-0040 0018-9391 |
| DOI: | 10.1109/tem.2019.2959701 |
| Popis: | Scheduling the recharging of electric vehicle fleets under different scenarios is an important but open problem. One important scenario is that vehicles travel at different speeds in different periods since traffic congestion is common in urban areas nowadays. Therefore, in this article, a novel time-dependent electric vehicle routing problem with congestion tolls is proposed. If a vehicle enters a peak period, a fixed congestion toll needs to be paid in this problem. A mixed integer linear programming model is established and an adaptive large neighborhood search (ALNS) heuristic is designed to solve the model. The model and solving method are validated and evaluated extensively with benchmark instances. Results indicate that a certain level of congestion tolls could prevent vehicles from entering peak periods and relieve road congestions significantly. Furthermore, the ALNS heuristic could provide much better solutions for the problem than typical optimization software, such as Gurobi, in much shorter running time. |
| Databáze: | OpenAIRE |
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