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Neural Computing and Applications

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01.12.2013 | Original Article

Two meta-heuristic algorithms for two-echelon location-routing problem with vehicle fleet capacity and maximum route length constraints

verfasst von: Vahid Majazi Dalfard, Mojtaba Kaveh, Nassim Ekram Nosratian

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2013

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Abstract

In the present research, a two-echelon location-routing problem with constraints of vehicle fleet capacity and maximum route length is considered. The problem’s objective is to determine the location and number of two types of capacitated facilities, the size of two different vehicle fleets, and the related routes on each echelon. Two algorithms hybrid genetic algorithm and simulated annealing are then applied to solve the problem. Results of numerical experiments show that the applied hybrid genetic and simulated annealing algorithms are much more effective than the solutions of the solved examples by the software LINGO. Finally, solutions of simulated annealing and hybrid genetic algorithms were compared with each other.

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Titel: Two meta-heuristic algorithms for two-echelon location-routing problem with vehicle fleet capacity and maximum route length constraints
verfasst von: Vahid Majazi Dalfard
Mojtaba Kaveh
Nassim Ekram Nosratian
Publikationsdatum: 01.12.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7-8/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-1190-0

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