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http://hdl.handle.net/1942/22929
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DC Field | Value | Language |
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dc.contributor.author | Masmoudi, Mohamed Amine | - |
dc.contributor.author | BRAEKERS, Kris | - |
dc.contributor.author | Masmoudi, Malek | - |
dc.contributor.author | Dammak, Abdelaziz | - |
dc.date.accessioned | 2016-12-21T09:18:24Z | - |
dc.date.available | 2016-12-21T09:18:24Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Computers & operations research, 81, p. 1-13 | - |
dc.identifier.issn | 0305-0548 | - |
dc.identifier.uri | http://hdl.handle.net/1942/22929 | - |
dc.description.abstract | This paper investigates the Heterogeneous Dial-A-Ride Problem (H-DARP) that consists of determining a vehicle route planning for heterogeneous users’ transportation with a heterogeneous fleet of vehicles. A hybrid Genetic Algorithm (GA) is proposed to solve the problem. Efficient construction heuristics, crossover operators and local search techniques, specifically tailored to the characteristics of the H-DARP, are provided. The proposed algorithm is tested on 92 benchmarks instances and 40 newly introduced larger instances. Computational experiments show the effectiveness of our approach compared to the current state-of-the-art algorithms for the DARP and H-DARP. When tested on the existing instances, we achieved average gaps of only 0.47% to the bestknown solutions for the DARP, and 0.05% to the optimal solutions for the H-DARP, compared to 0.85% and 0.10%, respectively, obtained by the current state-of-the-art algorithms. For the 40 newly generated instances, average gaps of the hybrid GA are 0.35% smaller compared to the current stateof-the-art method. Besides, our method provides best results for 31 of these instances and ties with the existing method on 8 other instances. | - |
dc.description.sponsorship | This work is partly supported by the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (research project COMEX, Combinatorial Optimization: Metaheuristics & Exact Methods). The authors thank the reviewers for their input, comments and suggestions. Also, the authors would like to thank Dr. Manar Hosny, Assistant Professor at King Saud University, for her valuable revision and English writing of the paper. | - |
dc.language.iso | en | - |
dc.rights | © 2016 Elsevier Ltd. All rights reserved. | - |
dc.subject.other | Heterogeneous Dial-A-Ride Problem (H-DARP); Genetic Algorithm (GA); construction heuristics; Local Search (LS); hybrid algorithm | - |
dc.title | A hybrid genetic algorithm for the heterogeneous dial-a-ride problem | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 13 | - |
dc.identifier.spage | 1 | - |
dc.identifier.volume | 81 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Masmoudi, MA (reprint author), Univ Sfax, Fac Econ & Management Sci, Lab Modeling & Optimizat Decis Ind & Logist Syst, Airport St,Km 4,POB 1088, Sfax 3018, Tunisia. masmoudi_aminero@hotmail.fr | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1016/j.cor.2016.12.008 | - |
dc.identifier.isi | 000394079400001 | - |
item.fulltext | With Fulltext | - |
item.accessRights | Open Access | - |
item.validation | ecoom 2018 | - |
item.contributor | Masmoudi, Mohamed Amine | - |
item.contributor | BRAEKERS, Kris | - |
item.contributor | Masmoudi, Malek | - |
item.contributor | Dammak, Abdelaziz | - |
item.fullcitation | Masmoudi, Mohamed Amine; BRAEKERS, Kris; Masmoudi, Malek & Dammak, Abdelaziz (2017) A hybrid genetic algorithm for the heterogeneous dial-a-ride problem. In: Computers & operations research, 81, p. 1-13. | - |
crisitem.journal.issn | 0305-0548 | - |
crisitem.journal.eissn | 1873-765X | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
HDARP 27-11.pdf | Peer-reviewed author version | 1.5 MB | Adobe PDF | View/Open |
1-s2.0-S0305054816303070-main.pdf Restricted Access | Published version | 896.24 kB | Adobe PDF | View/Open Request a copy |
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