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Hybrid adaptive large neighbourhood search algorithm for the mixed fleet heterogeneous dial-a-ride problem

  • The mixed fleet heterogeneous dial-a-ride problem (MF-HDARP) consists of designing vehicle routes for a set of users by using a mixed fleet including both heterogeneous coentional and alternative fuel vehicles. In addition, a vehicle is allowed to refuel from a fuel station to eliminate the risk of running out of fuel during its service. We propose an efficient hybrid adaptive large neighborhood search (hybrid ALNS) algorithm for the MF-HDARP. The computational experiments show that the algorithm produces high quality solutions on our generated instances and on HDARP benchmarks instances. Computational experiments also highlight that the newest components added to the standard ALNS algorithm enhance intensification and diversification during the search process.

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Metadaten
Document Type:Article
Language:English
Author:Mohamed Masmoudi, Manar Hosny, Emrah Demir, Erwin PeschORCiD
Center:Center for Advanced Studies in Management (CASiM)
DOI:https://doi.org/10.1007/s10732-019-09424-x
Parent Title (English):Journal of Heuristics
ISSN:1381-1231
Volume:26
Year of Completion:2020
First Page:83
Last Page:118
Tag:adaptive large neighborhood search algorithm; alternative fuel station; dial-a-ride problem; mixed vehicle fleet
Content Focus:Academic Audience
Peer Reviewed:Yes
Rankings:AJG Ranking / 3
VHB Ranking / B
SJR Ranking / Q2
Licence (German):License LogoUrheberrechtlich geschützt