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Facing the job shop scheduling problem wih hybrid evolutionary algorithms

Salto, Carolina et al · SEDICI UNLP · 2001

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Evolutionary algorithms (EAs) offer a robust approach to problem solving. EAs are extremely flexible and can be extended by incorporating alternative approaches to favour he search process. One way is to hybridize an evolutionary algorithm with standard local search procedures [10,11], such as hill climbing [12], simulated annealing [15] and tabu search [4]. Individual solutions can be improved using local techniques and then placed back in competition with other members of the population. The hybrid approach complements the properties of evolutionary algorithm and local search heuristic methods. An evolutionary algorithm is used to perform global search to escape from local optima, while local search is used to conduct fine-tuning. Eje: Inteligencia Computacional - Metaheurísticas Red de Universidades con Carreras en Informática (RedUNCI)

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APA 7

Salto, C. E. A. (2001). Facing the job shop scheduling problem wih hybrid evolutionary algorithms. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/21660

MLA

Salto, Carolina et al. Facing the job shop scheduling problem wih hybrid evolutionary algorithms. SEDICI UNLP, 2001. http://sedici.unlp.edu.ar/handle/10915/21660.

Chicago

Salto, Carolina et al. 2001. Facing the job shop scheduling problem wih hybrid evolutionary algorithms. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/21660.

Harvard

Salto, C. E. A. 2001, Facing the job shop scheduling problem wih hybrid evolutionary algorithms, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/21660 [Accessed 7 Aug. 2026].

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Title
Facing the job shop scheduling problem wih hybrid evolutionary algorithms
Author / contributors
Salto, Carolina et al
Publisher
SEDICI UNLP
Publication year
2001
Language
English

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