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

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

Gatica, Claudia R. et al · SEDICI UNLP · 2012

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Autore / responsabile

Gatica, Claudia R. et al

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SEDICI UNLP

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2012

Lingua

Inglés

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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. Eje: Workshop Agentes y sistemas inteligentes (WASI) Red de Universidades con Carreras en Informática (RedUNCI)

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APA 7

Gatica, C. R. E. A. (2012). Comparative study of trajectory metaheuristics for the resolution of scheduling problem of unrestricted parallel identical machines. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/23606

MLA

Gatica, Claudia R. et al. Comparative study of trajectory metaheuristics for the resolution of scheduling problem of unrestricted parallel identical machines. SEDICI UNLP, 2012. http://sedici.unlp.edu.ar/handle/10915/23606.

Chicago

Gatica, Claudia R. et al. 2012. Comparative study of trajectory metaheuristics for the resolution of scheduling problem of unrestricted parallel identical machines. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/23606.

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Gatica, C. R. E. A. 2012, Comparative study of trajectory metaheuristics for the resolution of scheduling problem of unrestricted parallel identical machines, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/23606 [Accessed 6 Aug. 2026].

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

Autore / collaboratori: Gatica, Claudia R. et al

Editore: SEDICI UNLP

Anno di pubblicazione: 2012

Lingua: Inglés

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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