Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm
Evolutionary algorithms have been widely used to solve large and complex optimisation problems. Cultural algorithms (CAs) are evolutionary algorithms that have been used to solve both single and, to a less extent, multiobjective optimisation problems. In order to solve these optimisation problems, C...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/745921 |
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| _version_ | 1849400416020725760 |
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| author | Carolina Lagos Broderick Crawford Enrique Cabrera Ricardo Soto José-Miguel Rubio Fernando Paredes |
| author_facet | Carolina Lagos Broderick Crawford Enrique Cabrera Ricardo Soto José-Miguel Rubio Fernando Paredes |
| author_sort | Carolina Lagos |
| collection | DOAJ |
| description | Evolutionary algorithms have been widely used to solve large and complex optimisation problems. Cultural algorithms (CAs) are evolutionary algorithms that have been used to solve both single and, to a less extent, multiobjective optimisation problems. In order to solve these optimisation problems, CAs make use of different strategies such as normative knowledge, historical knowledge, circumstantial knowledge, and among others. In this paper we present a comparison among CAs that make use of different evolutionary strategies; the first one implements a historical knowledge, the second one considers a circumstantial knowledge, and the third one implements a normative knowledge. These CAs are applied on a biobjective uncapacitated facility location problem (BOUFLP), the biobjective version of the well-known uncapacitated facility location problem. To the best of our knowledge, only few articles have applied evolutionary multiobjective algorithms on the BOUFLP and none of those has focused on the impact of the evolutionary strategy on the algorithm performance. Our biobjective cultural algorithm, called BOCA, obtains important improvements when compared to other well-known evolutionary biobjective optimisation algorithms such as PAES and NSGA-II. The conflicting objective functions considered in this study are cost minimisation and coverage maximisation. Solutions obtained by each algorithm are compared using a hypervolume S metric. |
| format | Article |
| id | doaj-art-87f9be7d67c948c39f5418bcbfc40408 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-87f9be7d67c948c39f5418bcbfc404082025-08-20T03:38:05ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/745921745921Comparing Evolutionary Strategies on a Biobjective Cultural AlgorithmCarolina Lagos0Broderick Crawford1Enrique Cabrera2Ricardo Soto3José-Miguel Rubio4Fernando Paredes5Escuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, ChileEscuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, ChileCIMFAV Facultad de Ingeniería, Universidad de Valparaíso, 2362735 Valparaíso, ChileEscuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, ChileEscuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, ChileEscuela de Ingeniería Industrial, Universidad Diego Portales, 8370109 Santiago, ChileEvolutionary algorithms have been widely used to solve large and complex optimisation problems. Cultural algorithms (CAs) are evolutionary algorithms that have been used to solve both single and, to a less extent, multiobjective optimisation problems. In order to solve these optimisation problems, CAs make use of different strategies such as normative knowledge, historical knowledge, circumstantial knowledge, and among others. In this paper we present a comparison among CAs that make use of different evolutionary strategies; the first one implements a historical knowledge, the second one considers a circumstantial knowledge, and the third one implements a normative knowledge. These CAs are applied on a biobjective uncapacitated facility location problem (BOUFLP), the biobjective version of the well-known uncapacitated facility location problem. To the best of our knowledge, only few articles have applied evolutionary multiobjective algorithms on the BOUFLP and none of those has focused on the impact of the evolutionary strategy on the algorithm performance. Our biobjective cultural algorithm, called BOCA, obtains important improvements when compared to other well-known evolutionary biobjective optimisation algorithms such as PAES and NSGA-II. The conflicting objective functions considered in this study are cost minimisation and coverage maximisation. Solutions obtained by each algorithm are compared using a hypervolume S metric.http://dx.doi.org/10.1155/2014/745921 |
| spellingShingle | Carolina Lagos Broderick Crawford Enrique Cabrera Ricardo Soto José-Miguel Rubio Fernando Paredes Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm The Scientific World Journal |
| title | Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm |
| title_full | Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm |
| title_fullStr | Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm |
| title_full_unstemmed | Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm |
| title_short | Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm |
| title_sort | comparing evolutionary strategies on a biobjective cultural algorithm |
| url | http://dx.doi.org/10.1155/2014/745921 |
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