Abstract
Due to environmental friendliness, electric vehicles have become more and more popular nowadays in the transportation system. For many express companies, it is more and more important to meet the predetermined time window of customers. The uncertainty in travel times often causes uncertain energy consumption and uncertain recharging time, thus electric vehicles may miss the time windows of customers. Therefore, this paper addresses the electric vehicle routing problem with time windows under travel time uncertainty, which aims to determine the optimal delivery strategy under travel time uncertainty. To solve this problem, a robust optimization model is built based on the route-dependent uncertainty sets. However, considering the complexity of the problem, the robust model can only solve few instances including the small number of customers. Thus, a hybrid metaheuristic consisting of the adaptive large neighborhood search algorithm and the local search algorithm is proposed. The results show that the algorithm can obtain the optimal solution for the small-sized instances and the large-sized instances.
| Original language | English |
|---|---|
| Article number | 012032 |
| Journal | Journal of Physics: Conference Series |
| Volume | 2095 |
| Issue number | 1 |
| DOIs | |
| State | Published - 22 Nov 2021 |
| Event | 2021 5th International Conference on Electrical, Automation and Mechanical Engineering, EAME 2021 - Guangzhou, Virtual, China Duration: 17 Sep 2021 → 18 Sep 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Robust optimization
- The adaptive large neighborhood search
- The electric vehicle routing problem
- The local search
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