A comparison of trajectory granular based algorithms for the location-routing problem with heterogeneous fleet (LRPH)
We consider the Location-Routing Problem with Heterogeneous Fleet (LRPH) in which the goal is to determine the depots to be opened, the customers to be assigned to each open depot, and the corresponding routes fulfilling the demand of the customers and by considering a heterogeneous fleet. We propos...
- Autores:
-
Bernal-Moyano, José Alfonso
Escobar Velasquez, John Willmer
Marín-Moreno, Cesar
Linfati, Rodrigo
Gatica, Gustavo
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60438
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60438
http://bdigital.unal.edu.co/58770/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Location-routing problem
heterogeneous fleet
simulated annealing
variable neighborhood search
probabilistic tabu search
metaheuristic algorithms
Problema de localización y ruteo
flota heterogénea
recocido simulado
búsqueda de vecindario variable
búsqueda tabú probabilística
algoritmos metaheurísticos
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | We consider the Location-Routing Problem with Heterogeneous Fleet (LRPH) in which the goal is to determine the depots to be opened, the customers to be assigned to each open depot, and the corresponding routes fulfilling the demand of the customers and by considering a heterogeneous fleet. We propose a comparison of granular approaches of Simulated Annealing (GSA), of Variable Neighborhood Search (GVNS) and of a probabilistic Tabu Search (pGTS) for the LRPH. Thus, the proposed approaches consider a subset of the search space in which non-favorable movements are discarded regarding a granularity factor. The proposed algorithms are experimentally compared for the solution of the LRPH, by taking into account the CPU time and the quality of the solutions obtained on the instances adapted from the literature. The computational results show that algorithm GSA is able to obtain high quality solutions within short CPU times, improving the results obtained by the other proposed approaches. |
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