Resolving the manufacturing cell design problem using the flower pollination algorithm

Ricardo Soto; Broderick Crawford; Rodrigo Olivares; Michele De Conti; Ronald Rubio; Boris Almonacid; Stefanie Niklander

doi:10.1007/978-3-319-49397-8_16

Resolving the manufacturing cell design problem using the flower pollination algorithm

Ricardo Soto, Broderick Crawford, Rodrigo Olivares, Michele De Conti, Ronald Rubio, Boris Almonacid, Stefanie Niklander

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The Manufacturing cell design problem focuses on the creation of an optimal distribution of the machinery on a productive plant, through the creation of highly independent cells where the parts of certain products are processed. The main objective is to reduce the movements between this cells, decreasing production times, costs and getting other advantages. To find solutions to this problem, in this paper, the usage of the Flower Pollination Algorithm is proposed, which is one of the many nature-based algorithms, which in this case is inspired in the Pollination of the flowers, and has shown great capacities in the resolution of complex problems. Experimental results are shown, with 90 instances taken from Boctor’s experiments, where the optimum is achieved in all them.

Original language	English
Title of host publication	Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings
Editors	Frieder Stolzenburg, Abhaya Nayak, Fangzhen Lin, Chattrakul Sombattheera
Publisher	Springer Verlag
Pages	184-195
Number of pages	12
ISBN (Print)	9783319493961
DOIs	https://doi.org/10.1007/978-3-319-49397-8_16
State	Published - 2016
Externally published	Yes
Event	10th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI 2016 - Chiang Mai, Thailand Duration: 7 Dec 2016 → 9 Dec 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10053 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI 2016
Country/Territory	Thailand
City	Chiang Mai
Period	7/12/16 → 9/12/16

Keywords

Flower pollination algorithm
Manufacturing cell design problem
Metaheuristics
Optimization

Access to Document

10.1007/978-3-319-49397-8_16

Cite this

Soto, R., Crawford, B., Olivares, R., De Conti, M., Rubio, R., Almonacid, B., & Niklander, S. (2016). Resolving the manufacturing cell design problem using the flower pollination algorithm. In F. Stolzenburg, A. Nayak, F. Lin, & C. Sombattheera (Eds.), Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings (pp. 184-195). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10053 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-49397-8_16

Soto, Ricardo ; Crawford, Broderick ; Olivares, Rodrigo et al. / Resolving the manufacturing cell design problem using the flower pollination algorithm. Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings. editor / Frieder Stolzenburg ; Abhaya Nayak ; Fangzhen Lin ; Chattrakul Sombattheera. Springer Verlag, 2016. pp. 184-195 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{086923af45e846a0b7366d5732d04df0,

title = "Resolving the manufacturing cell design problem using the flower pollination algorithm",

abstract = "The Manufacturing cell design problem focuses on the creation of an optimal distribution of the machinery on a productive plant, through the creation of highly independent cells where the parts of certain products are processed. The main objective is to reduce the movements between this cells, decreasing production times, costs and getting other advantages. To find solutions to this problem, in this paper, the usage of the Flower Pollination Algorithm is proposed, which is one of the many nature-based algorithms, which in this case is inspired in the Pollination of the flowers, and has shown great capacities in the resolution of complex problems. Experimental results are shown, with 90 instances taken from Boctor{\textquoteright}s experiments, where the optimum is achieved in all them.",

keywords = "Flower pollination algorithm, Manufacturing cell design problem, Metaheuristics, Optimization",

author = "Ricardo Soto and Broderick Crawford and Rodrigo Olivares and {De Conti}, Michele and Ronald Rubio and Boris Almonacid and Stefanie Niklander",

note = "Funding Information: Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1160455, Broderick Crawford is supported by Grant CONICYT/FONDECYT/REGULAR/1140897, Rodrigo Olivares is supported by Postgraduate Grant Pontificia Universidad Cat{\'o}lica de Valpara{\'i}so, Chile (INF-PUCV 2015), and Boris Almonacid is supported by Postgraduate Grant Pontificia Universidad Cat{\'o}lica de Valpara{\'i}so, Chile (VRIEA-PUCV 2016 and INF-PUCV 2015), by Animal Behavior Society, USA (Developing Nations Research Awards 2016) and by Ph.D (h.c) Sonia Alvarez, Chile. Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; null ; Conference date: 07-12-2016 Through 09-12-2016",

year = "2016",

doi = "10.1007/978-3-319-49397-8_16",

language = "English",

isbn = "9783319493961",

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

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pages = "184--195",

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booktitle = "Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings",

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Soto, R , Crawford, B, Olivares, R, De Conti, M, Rubio, R, Almonacid, B & Niklander, S 2016, Resolving the manufacturing cell design problem using the flower pollination algorithm. in F Stolzenburg, A Nayak, F Lin & C Sombattheera (eds), Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10053 LNAI, Springer Verlag, pp. 184-195, 10th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI 2016, Chiang Mai, Thailand, 7/12/16. https://doi.org/10.1007/978-3-319-49397-8_16

Resolving the manufacturing cell design problem using the flower pollination algorithm. / Soto, Ricardo ; Crawford, Broderick; Olivares, Rodrigo et al.

Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings. ed. / Frieder Stolzenburg; Abhaya Nayak; Fangzhen Lin; Chattrakul Sombattheera. Springer Verlag, 2016. p. 184-195 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10053 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Resolving the manufacturing cell design problem using the flower pollination algorithm

AU - Soto, Ricardo

AU - Crawford, Broderick

AU - Olivares, Rodrigo

AU - De Conti, Michele

AU - Rubio, Ronald

AU - Almonacid, Boris

AU - Niklander, Stefanie

N1 - Funding Information: Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1160455, Broderick Crawford is supported by Grant CONICYT/FONDECYT/REGULAR/1140897, Rodrigo Olivares is supported by Postgraduate Grant Pontificia Universidad Católica de Valparaíso, Chile (INF-PUCV 2015), and Boris Almonacid is supported by Postgraduate Grant Pontificia Universidad Católica de Valparaíso, Chile (VRIEA-PUCV 2016 and INF-PUCV 2015), by Animal Behavior Society, USA (Developing Nations Research Awards 2016) and by Ph.D (h.c) Sonia Alvarez, Chile. Publisher Copyright: © Springer International Publishing AG 2016.

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AB - The Manufacturing cell design problem focuses on the creation of an optimal distribution of the machinery on a productive plant, through the creation of highly independent cells where the parts of certain products are processed. The main objective is to reduce the movements between this cells, decreasing production times, costs and getting other advantages. To find solutions to this problem, in this paper, the usage of the Flower Pollination Algorithm is proposed, which is one of the many nature-based algorithms, which in this case is inspired in the Pollination of the flowers, and has shown great capacities in the resolution of complex problems. Experimental results are shown, with 90 instances taken from Boctor’s experiments, where the optimum is achieved in all them.

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Soto R , Crawford B, Olivares R, De Conti M, Rubio R, Almonacid B et al. Resolving the manufacturing cell design problem using the flower pollination algorithm. In Stolzenburg F, Nayak A, Lin F, Sombattheera C, editors, Multi-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings. Springer Verlag. 2016. p. 184-195. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-49397-8_16

Resolving the manufacturing cell design problem using the flower pollination algorithm

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