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

Mohamed Amine Masmoudi; Manar Hosny; Emrah Demir; Erwin Pesch

doi:10.1007/s10732-019-09424-x

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

Mohamed Amine Masmoudi, Manar Hosny, Emrah Demir, Erwin Pesch

Management Science & Engineering

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

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 conventional 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.

Original language	British English
Pages (from-to)	83-118
Number of pages	36
Journal	Journal of Heuristics
Volume	26
Issue number	1
DOIs	https://doi.org/10.1007/s10732-019-09424-x
State	Published - 1 Feb 2020

Keywords

Adaptive large neighborhood search algorithm
Alternative fuel station
Dial-a-ride problem
Mixed vehicle fleet

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abstract = "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 conventional 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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Hybrid adaptive large neighborhood search algorithm for the mixed fleet heterogeneous dial-a-ride problem

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Keywords

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