Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design

Orlando Duran; Nibaldo Rodriguez; Luiz Airton Consalter

doi:10.1007/978-3-540-88636-548

Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design

Orlando Duran, Nibaldo Rodriguez, Luiz Airton Consalter

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

5 Citas (Scopus)

Resumen

This paper proposes an hybrid algorithm for Manufacturing Cell Formation. The two techniques that are combined to address this problem correspond to Particle Swarm Optimization (PSO) and a Data Mining Clustering application. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. A maximum cell size is imposed and the number of cell is parameterizable. Some published exact results have been used as benchmarks to assess the proposed algorithm. The computational results show that the proposed algorithm is able to find the optimal solutions on almost all instances with low variability and stability.

Idioma original	Inglés
Título de la publicación alojada	MICAI 2008
Subtítulo de la publicación alojada	Advances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings
Páginas	503-512
Número de páginas	10
DOI	https://doi.org/10.1007/978-3-540-88636-548
Estado	Publicada - 2008
Publicado de forma externa	Sí
Evento	7th Mexican International Conference on Artificial Intelligence, MICAI 2008 - Atizapan de Zaragoza, México Duración: 27 oct. 2008 → 31 oct. 2008

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	5317 LNAI
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	7th Mexican International Conference on Artificial Intelligence, MICAI 2008
País/Territorio	México
Ciudad	Atizapan de Zaragoza
Período	27/10/08 → 31/10/08

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10.1007/978-3-540-88636-548

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Duran, O., Rodriguez, N., & Consalter, L. A. (2008). Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design. En MICAI 2008: Advances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings (pp. 503-512). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5317 LNAI). https://doi.org/10.1007/978-3-540-88636-548

Duran, Orlando ; Rodriguez, Nibaldo ; Consalter, Luiz Airton. / Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design. MICAI 2008: Advances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings. 2008. pp. 503-512 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design",

abstract = "This paper proposes an hybrid algorithm for Manufacturing Cell Formation. The two techniques that are combined to address this problem correspond to Particle Swarm Optimization (PSO) and a Data Mining Clustering application. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. A maximum cell size is imposed and the number of cell is parameterizable. Some published exact results have been used as benchmarks to assess the proposed algorithm. The computational results show that the proposed algorithm is able to find the optimal solutions on almost all instances with low variability and stability.",

keywords = "Machine grouping, Manufacturing cells, Particle swarm optimization",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Duran, O , Rodriguez, N & Consalter, LA 2008, Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design. En MICAI 2008: Advances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5317 LNAI, pp. 503-512, 7th Mexican International Conference on Artificial Intelligence, MICAI 2008, Atizapan de Zaragoza, México, 27/10/08. https://doi.org/10.1007/978-3-540-88636-548

Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design. / Duran, Orlando ; Rodriguez, Nibaldo; Consalter, Luiz Airton.

MICAI 2008: Advances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings. 2008. p. 503-512 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5317 LNAI).

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AU - Duran, Orlando

AU - Rodriguez, Nibaldo

AU - Consalter, Luiz Airton

PY - 2008

Y1 - 2008

N2 - This paper proposes an hybrid algorithm for Manufacturing Cell Formation. The two techniques that are combined to address this problem correspond to Particle Swarm Optimization (PSO) and a Data Mining Clustering application. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. A maximum cell size is imposed and the number of cell is parameterizable. Some published exact results have been used as benchmarks to assess the proposed algorithm. The computational results show that the proposed algorithm is able to find the optimal solutions on almost all instances with low variability and stability.

AB - This paper proposes an hybrid algorithm for Manufacturing Cell Formation. The two techniques that are combined to address this problem correspond to Particle Swarm Optimization (PSO) and a Data Mining Clustering application. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. A maximum cell size is imposed and the number of cell is parameterizable. Some published exact results have been used as benchmarks to assess the proposed algorithm. The computational results show that the proposed algorithm is able to find the optimal solutions on almost all instances with low variability and stability.

KW - Machine grouping

KW - Manufacturing cells

KW - Particle swarm optimization

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U2 - 10.1007/978-3-540-88636-548

DO - 10.1007/978-3-540-88636-548

M3 - Conference contribution

AN - SCOPUS:57049094913

SN - 3540886354

SN - 9783540886358

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Duran O , Rodriguez N, Consalter LA. Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design. En MICAI 2008: Advances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings. 2008. p. 503-512. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-88636-548

Hybridization of PSO and a discrete position update scheme techniques for manufacturing cell design

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