Masmoudi, Mohamed Amine, Hosny, Manar, Demir, Emrah ![]() ![]() |
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Abstract
The Dial-a-Ride Problem (DARP) consists of designing vehicle routes and schedules for customers with special needs and/or disabilities. The DARP with Electric Vehicles and battery swapping stations (DARP-EV) concerns scheduling a fleet of EVs to serve a set of pre-specified transport requests during a certain planning horizon. In addition, EVs can be recharged by swapping their batteries with charged ones from any battery-swap stations. We propose three enhanced Evolutionary Variable Neighborhood Search (EVO-VNS) algorithms to solve the DARP-EV. Extensive computational experiments highlight the relevance of the problem and confirm the efficiency of the proposed EVO-VNS algorithms in producing high quality solutions.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Business (Including Economics) |
Additional Information: | Released with a Creative Commons Attribution Non-Commercial No Derivatives License (CC BY-NC-ND) |
Publisher: | Elsevier |
ISSN: | 1366-5545 |
Date of First Compliant Deposit: | 11 August 2018 |
Date of Acceptance: | 10 August 2018 |
Last Modified: | 19 Nov 2024 20:00 |
URI: | https://orca.cardiff.ac.uk/id/eprint/114129 |
Citation Data
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