Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorit...

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Detalles Bibliográficos
Autores principales: Wang, Peng, Zhu, Zhouquan, Huang, Shuai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872433/
https://www.ncbi.nlm.nih.gov/pubmed/24385879
http://dx.doi.org/10.1155/2013/378515
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author Wang, Peng
Zhu, Zhouquan
Huang, Shuai
author_facet Wang, Peng
Zhu, Zhouquan
Huang, Shuai
author_sort Wang, Peng
collection PubMed
description This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions.
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spelling pubmed-38724332014-01-02 Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization Wang, Peng Zhu, Zhouquan Huang, Shuai ScientificWorldJournal Research Article This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions. Hindawi Publishing Corporation 2013-12-09 /pmc/articles/PMC3872433/ /pubmed/24385879 http://dx.doi.org/10.1155/2013/378515 Text en Copyright © 2013 Peng Wang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Peng
Zhu, Zhouquan
Huang, Shuai
Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization
title Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization
title_full Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization
title_fullStr Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization
title_full_unstemmed Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization
title_short Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization
title_sort seven-spot ladybird optimization: a novel and efficient metaheuristic algorithm for numerical optimization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872433/
https://www.ncbi.nlm.nih.gov/pubmed/24385879
http://dx.doi.org/10.1155/2013/378515
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AT zhuzhouquan sevenspotladybirdoptimizationanovelandefficientmetaheuristicalgorithmfornumericaloptimization
AT huangshuai sevenspotladybirdoptimizationanovelandefficientmetaheuristicalgorithmfornumericaloptimization

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