2221. A Matheuristic Method for Heterogeneous Electric Vehicle Routing Problem with Load Dependent Discharging
Invited abstract in session MC-58: Electric Vehicles, stream Vehicle Routing and Logistics.
Monday, 12:30-14:00Room: Liberty 1.13
Authors (first author is the speaker)
| 1. | Ismail Gokay Dogan
|
| School of Computer Science, University of Nottingham |
Abstract
Electric vehicles (EVs) are a transformative asset in logistics and transportation, and aid to improve sustainability. Their use requires effective route planning methods that consider range limitations and charging decisions. The Heterogeneous Fleet Electric Vehicle Routing Problem with Load Dependent Discharging (HFEVRP-LD) optimises routing and charging decisions for a fleet of EVs with varying acquisition costs, energy consumption rates, battery capacities, and load capacities. The problem considers time windows, service durations, and a load-dependent energy consumption model. The objective is to minimise the total cost of vehicle acquisition and energy consumption. This study proposes a matheuristic that combines Adaptive Large Neighborhood Search (ALNS) with an exact method to solve HFEVRP-LD. The ALNS explores diverse neighborhoods through multiple destroy-repair mechanisms, and employs an exact approach to repair charging and vehicle selection decisions. Results of computational experiments on benchmark instances demonstrate the effectiveness of the proposed method.
Keywords
- Vehicle Routing
- Transportation
- Metaheuristics
Status: accepted
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