An Evolutionary Approach to solve the ...
Document type :
Compte-rendu et recension critique d'ouvrage
DOI :
Title :
An Evolutionary Approach to solve the Dynamic Multi-Hop Ridematching Problem
Author(s) :
Ben Cheikh, Sondes [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Tahon, Christian [Auteur]
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]
Hammadi, Slim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Tahon, Christian [Auteur]
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]
Hammadi, Slim [Auteur]
Journal title :
SIMULATION: Transactions of The Society for Modeling and Simulation International
Pages :
3-19
Publisher :
SAGE Publications
Publication date :
2016-09-30
ISSN :
0037-5497
English keyword(s) :
dynamic coding
evolutionary algorithm
Multihop ridesharing
optimization
evolutionary algorithm
Multihop ridesharing
optimization
HAL domain(s) :
Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
The multihop ridesharing system generates a ridematching solution with an arbitrary number of transfers that respects personal preferences of the users and their time constraints with detour willingness. As it is considered ...
Show more >The multihop ridesharing system generates a ridematching solution with an arbitrary number of transfers that respects personal preferences of the users and their time constraints with detour willingness. As it is considered to be NP-complete, an efficient metaheuristic is required in the application to solve the dynamic multihop ridematching problem. In this context, a novel approach, called Metaheuristics Approach Based on Controlled Genetic Operators (MACGeO), which is supported by an original dynamic coding, is developed to address the multihop ridematching problem. The performance of the proposed approach is measured via simulation scenarios, which feature various numbers of carpool drivers (vehicles) and riders (passengers). Experimental results show that the multihop ridematching could greatly increase the number of matched requests while minimizing the number of vehicles required. © The Author(s) 2016.Show less >
Show more >The multihop ridesharing system generates a ridematching solution with an arbitrary number of transfers that respects personal preferences of the users and their time constraints with detour willingness. As it is considered to be NP-complete, an efficient metaheuristic is required in the application to solve the dynamic multihop ridematching problem. In this context, a novel approach, called Metaheuristics Approach Based on Controlled Genetic Operators (MACGeO), which is supported by an original dynamic coding, is developed to address the multihop ridematching problem. The performance of the proposed approach is measured via simulation scenarios, which feature various numbers of carpool drivers (vehicles) and riders (passengers). Experimental results show that the multihop ridematching could greatly increase the number of matched requests while minimizing the number of vehicles required. © The Author(s) 2016.Show less >
Language :
Anglais
Popular science :
Non
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