A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem (2022)
- Authors:
- Autor USP: CONTRERAS, RODRIGO COLNAGO - ICMC
- Unidade: ICMC
- DOI: 10.3390/s22124561
- Subjects: ALGORITMOS GENÉTICOS; OTIMIZAÇÃO COMBINATÓRIA
- Keywords: evolutionary algorithm; genetic improvement; job shop scheduling problem
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
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ABNT
VIANA, Monique Simplicio e CONTRERAS, Rodrigo Colnago e MORANDIN JUNIOR, Orides. A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem. Sensors, v. 22, p. 1-26, 2022Tradução . . Disponível em: https://doi.org/10.3390/s22124561. Acesso em: 10 fev. 2026. -
APA
Viana, M. S., Contreras, R. C., & Morandin Junior, O. (2022). A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem. Sensors, 22, 1-26. doi:10.3390/s22124561 -
NLM
Viana MS, Contreras RC, Morandin Junior O. A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem [Internet]. Sensors. 2022 ; 22 1-26.[citado 2026 fev. 10 ] Available from: https://doi.org/10.3390/s22124561 -
Vancouver
Viana MS, Contreras RC, Morandin Junior O. A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem [Internet]. Sensors. 2022 ; 22 1-26.[citado 2026 fev. 10 ] Available from: https://doi.org/10.3390/s22124561 - Predição e análise visual de conjuntos de redes de conexões entre sinais suaves: aplicações em dados médicos de AVC
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Informações sobre o DOI: 10.3390/s22124561 (Fonte: oaDOI API)
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