Comparative study of trajectory metaheuristics for the resolution of scheduling problem of unrestricted parallel identical machines

In this paper we present a comparative study of four trajectory metaheuristics or single-solution based metaheuristics (S-meta heuristics): Iterated Local Search (ILS), Greedy Randomized Adaptive Search Procedure (GRASP), Variable Neighborhood Search (VNS) and Simulated Annealing (SA). The metaheuri...

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Detalles Bibliográficos
Autores principales: Gatica, Claudia R., Esquivel, Susana Cecilia, Leguizamón, Guillermo
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2012
Materias:
Ciencias Informáticas
Iterated Local Search
Greedy Randomized Adaptive Search Procedure
Variable Neighborhood Search
Simulated Annealing
Parallel Machines Scheduling
Maximum Tardiness
Statistical Nonparametric Tests
Scheduling
Simulation
Parallel
Intelligent agents
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23606
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
Descripción
Sumario:In this paper we present a comparative study of four trajectory metaheuristics or single-solution based metaheuristics (S-meta heuristics): Iterated Local Search (ILS), Greedy Randomized Adaptive Search Procedure (GRASP), Variable Neighborhood Search (VNS) and Simulated Annealing (SA). The metaheuristics were used to minimize the Maximum Tardiness (Tmax) for unrestricted parallel identical machine scheduling (Pm) problem, which is considered as NP-Hard problem. The results obtained through experimentation show that SA was the best behaved.

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