A cultural algorithm applied in a bi-objective uncapacitated facility location problem

Guillermo Cabrera; José Miguel Rubio; Daniela Díaz; Boris Fernández; Claudio Cubillos; Ricardo Soto

doi:10.1007/978-3-642-19893-9_33

A cultural algorithm applied in a bi-objective uncapacitated facility location problem

Guillermo Cabrera, José Miguel Rubio, Daniela Díaz, Boris Fernández, Claudio Cubillos, Ricardo Soto

SCHOOL OF COMPUTER ENGINEERING

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

2 Scopus citations

Abstract

Cultural Algorithms (CAs) are one of the metaheuristics which can be adapted in order to work in multi-objectives optimization environments. On the other hand, Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and particularly Uncapacitated Facility Location Problem (UFLP) are well know problems in literature. However, only few articles have applied evolutionary multi-objective (EMO) algorithms to these problems and articles presenting CAs applied to the BOUFLP have not been found. In this article we presents a Bi-Objective Cultural Algorithm (BOCA) which was applied to the Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and it obtain an important improvement in comparison with other well-know EMO algorithms such as PAES and NSGA-II. The considered criteria were cost minimization and coverage maximization. The different solutions obtained with the CA were compared using an hypervolume S metric.

Original language	English
Title of host publication	Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Proceedings
Pages	477-491
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-642-19893-9_33
State	Published - 2011
Event	6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011 - Ouro Preto, Brazil Duration: 5 Apr 2011 → 8 Apr 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6576 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011
Country/Territory	Brazil
City	Ouro Preto
Period	5/04/11 → 8/04/11

Keywords

Bi-Objective Cultural Algorithm
Bi-Objective Uncapacitated Facility Location Problem
Evolutionary Multi-Objective Optimization
S metric

Access to Document

10.1007/978-3-642-19893-9_33

Cite this

Cabrera, G., Rubio, J. M., Díaz, D., Fernández, B., Cubillos, C., & Soto, R. (2011). A cultural algorithm applied in a bi-objective uncapacitated facility location problem. In Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Proceedings (pp. 477-491). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6576 LNCS). https://doi.org/10.1007/978-3-642-19893-9_33

Cabrera, Guillermo ; Rubio, José Miguel ; Díaz, Daniela et al. / A cultural algorithm applied in a bi-objective uncapacitated facility location problem. Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Proceedings. 2011. pp. 477-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Cultural Algorithms (CAs) are one of the metaheuristics which can be adapted in order to work in multi-objectives optimization environments. On the other hand, Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and particularly Uncapacitated Facility Location Problem (UFLP) are well know problems in literature. However, only few articles have applied evolutionary multi-objective (EMO) algorithms to these problems and articles presenting CAs applied to the BOUFLP have not been found. In this article we presents a Bi-Objective Cultural Algorithm (BOCA) which was applied to the Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and it obtain an important improvement in comparison with other well-know EMO algorithms such as PAES and NSGA-II. The considered criteria were cost minimization and coverage maximization. The different solutions obtained with the CA were compared using an hypervolume S metric.",

keywords = "Bi-Objective Cultural Algorithm, Bi-Objective Uncapacitated Facility Location Problem, Evolutionary Multi-Objective Optimization, S metric",

author = "Guillermo Cabrera and Rubio, {Jos{\'e} Miguel} and Daniela D{\'i}az and Boris Fern{\'a}ndez and Claudio Cubillos and Ricardo Soto",

year = "2011",

doi = "10.1007/978-3-642-19893-9_33",

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Cabrera, G, Rubio, JM, Díaz, D, Fernández, B, Cubillos, C & Soto, R 2011, A cultural algorithm applied in a bi-objective uncapacitated facility location problem. in Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6576 LNCS, pp. 477-491, 6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011, Ouro Preto, Brazil, 5/04/11. https://doi.org/10.1007/978-3-642-19893-9_33

A cultural algorithm applied in a bi-objective uncapacitated facility location problem. / Cabrera, Guillermo; Rubio, José Miguel; Díaz, Daniela et al.
Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Proceedings. 2011. p. 477-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6576 LNCS).

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

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AU - Rubio, José Miguel

AU - Díaz, Daniela

AU - Fernández, Boris

AU - Cubillos, Claudio

AU - Soto, Ricardo

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AB - Cultural Algorithms (CAs) are one of the metaheuristics which can be adapted in order to work in multi-objectives optimization environments. On the other hand, Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and particularly Uncapacitated Facility Location Problem (UFLP) are well know problems in literature. However, only few articles have applied evolutionary multi-objective (EMO) algorithms to these problems and articles presenting CAs applied to the BOUFLP have not been found. In this article we presents a Bi-Objective Cultural Algorithm (BOCA) which was applied to the Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and it obtain an important improvement in comparison with other well-know EMO algorithms such as PAES and NSGA-II. The considered criteria were cost minimization and coverage maximization. The different solutions obtained with the CA were compared using an hypervolume S metric.

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Cabrera G, Rubio JM, Díaz D, Fernández B, Cubillos C , Soto R. A cultural algorithm applied in a bi-objective uncapacitated facility location problem. In Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Proceedings. 2011. p. 477-491. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-19893-9_33

A cultural algorithm applied in a bi-objective uncapacitated facility location problem

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