An artificial fish swarm optimization algorithm to solve set covering problem

Broderick Crawford; Ricardo Soto; Eduardo Olguín; Sebastián Mansilla Villablanca; Álvaro Gómez Rubio; Adrián Jaramillo; Juan Salas

doi:10.1007/978-3-319-42007-3_76

An artificial fish swarm optimization algorithm to solve set covering problem

Broderick Crawford, Ricardo Soto, Eduardo Olguín, Sebastián Mansilla Villablanca, Álvaro Gómez Rubio, Adrián Jaramillo, Juan Salas

SCHOOL OF COMPUTER ENGINEERING

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

2 Scopus citations

Abstract

The Set Covering Problem (SCP) consists in finding a set of solutions that allow to cover a set of necessities with the minor possible cost. There are many applications of this problem such as rolling production lines or installation of certain services like hospitals. SCP has been solved before with different algorithms like genetic algorithm, cultural algorithm or firefly algorithm among others. The objective of this paper is to show the performance of an Artificial Fish Swarm Algorithm (AFSA) in order to solve SCP. This algorithm, simulates the behavior of a fish shoal inside water and it uses a population of points in space to represent the position of a fish in the shoal. Here we show a study of its simplified version of AFSA in a binary domain with its modifications applied to SCP. This method was tested on SCP benchmark instances from OR-Library website.

Original language	English
Title of host publication	Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings
Editors	Moonis Ali, Hamido Fujita, Jun Sasaki, Masaki Kurematsu, Ali Selamat
Publisher	Springer Verlag
Pages	892-903
Number of pages	12
ISBN (Print)	9783319420066
DOIs	https://doi.org/10.1007/978-3-319-42007-3_76
State	Published - 2016
Event	29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016 - Morioka, Japan Duration: 2 Aug 2016 → 4 Aug 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9799
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016
Country/Territory	Japan
City	Morioka
Period	2/08/16 → 4/08/16

Keywords

Artificial fish swarm optimization algorithm
Combinatorial optimization
Metaheuristics
Set covering problem

Access to Document

10.1007/978-3-319-42007-3_76

Cite this

Crawford, B., Soto, R., Olguín, E., Villablanca, S. M., Rubio, Á. G., Jaramillo, A., & Salas, J. (2016). An artificial fish swarm optimization algorithm to solve set covering problem. In M. Ali, H. Fujita, J. Sasaki, M. Kurematsu, & A. Selamat (Eds.), Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings (pp. 892-903). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9799). Springer Verlag. https://doi.org/10.1007/978-3-319-42007-3_76

Crawford, Broderick ; Soto, Ricardo ; Olguín, Eduardo et al. / An artificial fish swarm optimization algorithm to solve set covering problem. Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings. editor / Moonis Ali ; Hamido Fujita ; Jun Sasaki ; Masaki Kurematsu ; Ali Selamat. Springer Verlag, 2016. pp. 892-903 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An artificial fish swarm optimization algorithm to solve set covering problem",

abstract = "The Set Covering Problem (SCP) consists in finding a set of solutions that allow to cover a set of necessities with the minor possible cost. There are many applications of this problem such as rolling production lines or installation of certain services like hospitals. SCP has been solved before with different algorithms like genetic algorithm, cultural algorithm or firefly algorithm among others. The objective of this paper is to show the performance of an Artificial Fish Swarm Algorithm (AFSA) in order to solve SCP. This algorithm, simulates the behavior of a fish shoal inside water and it uses a population of points in space to represent the position of a fish in the shoal. Here we show a study of its simplified version of AFSA in a binary domain with its modifications applied to SCP. This method was tested on SCP benchmark instances from OR-Library website.",

keywords = "Artificial fish swarm optimization algorithm, Combinatorial optimization, Metaheuristics, Set covering problem",

author = "Broderick Crawford and Ricardo Soto and Eduardo Olgu{\'i}n and Villablanca, {Sebasti{\'a}n Mansilla} and Rubio, {{\'A}lvaro G{\'o}mez} and Adri{\'a}n Jaramillo and Juan Salas",

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doi = "10.1007/978-3-319-42007-3_76",

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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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editor = "Moonis Ali and Hamido Fujita and Jun Sasaki and Masaki Kurematsu and Ali Selamat",

booktitle = "Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings",

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Crawford, B , Soto, R, Olguín, E, Villablanca, SM, Rubio, ÁG, Jaramillo, A & Salas, J 2016, An artificial fish swarm optimization algorithm to solve set covering problem. in M Ali, H Fujita, J Sasaki, M Kurematsu & A Selamat (eds), Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9799, Springer Verlag, pp. 892-903, 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Morioka, Japan, 2/08/16. https://doi.org/10.1007/978-3-319-42007-3_76

An artificial fish swarm optimization algorithm to solve set covering problem. / Crawford, Broderick ; Soto, Ricardo; Olguín, Eduardo et al.
Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings. ed. / Moonis Ali; Hamido Fujita; Jun Sasaki; Masaki Kurematsu; Ali Selamat. Springer Verlag, 2016. p. 892-903 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9799).

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

TY - GEN

T1 - An artificial fish swarm optimization algorithm to solve set covering problem

AU - Crawford, Broderick

AU - Soto, Ricardo

AU - Olguín, Eduardo

AU - Villablanca, Sebastián Mansilla

AU - Rubio, Álvaro Gómez

AU - Jaramillo, Adrián

AU - Salas, Juan

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - The Set Covering Problem (SCP) consists in finding a set of solutions that allow to cover a set of necessities with the minor possible cost. There are many applications of this problem such as rolling production lines or installation of certain services like hospitals. SCP has been solved before with different algorithms like genetic algorithm, cultural algorithm or firefly algorithm among others. The objective of this paper is to show the performance of an Artificial Fish Swarm Algorithm (AFSA) in order to solve SCP. This algorithm, simulates the behavior of a fish shoal inside water and it uses a population of points in space to represent the position of a fish in the shoal. Here we show a study of its simplified version of AFSA in a binary domain with its modifications applied to SCP. This method was tested on SCP benchmark instances from OR-Library website.

AB - The Set Covering Problem (SCP) consists in finding a set of solutions that allow to cover a set of necessities with the minor possible cost. There are many applications of this problem such as rolling production lines or installation of certain services like hospitals. SCP has been solved before with different algorithms like genetic algorithm, cultural algorithm or firefly algorithm among others. The objective of this paper is to show the performance of an Artificial Fish Swarm Algorithm (AFSA) in order to solve SCP. This algorithm, simulates the behavior of a fish shoal inside water and it uses a population of points in space to represent the position of a fish in the shoal. Here we show a study of its simplified version of AFSA in a binary domain with its modifications applied to SCP. This method was tested on SCP benchmark instances from OR-Library website.

KW - Artificial fish swarm optimization algorithm

KW - Combinatorial optimization

KW - Metaheuristics

KW - Set covering problem

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DO - 10.1007/978-3-319-42007-3_76

M3 - Conference contribution

AN - SCOPUS:84978863610

SN - 9783319420066

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

SP - 892

EP - 903

BT - Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings

A2 - Ali, Moonis

A2 - Fujita, Hamido

A2 - Sasaki, Jun

A2 - Kurematsu, Masaki

A2 - Selamat, Ali

PB - Springer Verlag

T2 - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016

Y2 - 2 August 2016 through 4 August 2016

ER -

Crawford B , Soto R, Olguín E, Villablanca SM, Rubio ÁG, Jaramillo A et al. An artificial fish swarm optimization algorithm to solve set covering problem. In Ali M, Fujita H, Sasaki J, Kurematsu M, Selamat A, editors, Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings. Springer Verlag. 2016. p. 892-903. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-42007-3_76

An artificial fish swarm optimization algorithm to solve set covering problem

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