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A new optimization algorithm based on mimicking the voting process for leader selection
Stochastic-based optimization algorithms are effective approaches to addressing optimization challenges. In this article, a new optimization algorithm called the Election-Based Optimization Algorithm (EBOA) was developed that mimics the voting process to select the leader. The fundamental inspiratio...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9138015/ https://www.ncbi.nlm.nih.gov/pubmed/35634108 http://dx.doi.org/10.7717/peerj-cs.976 |
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author | Trojovský, Pavel Dehghani, Mohammad |
author_facet | Trojovský, Pavel Dehghani, Mohammad |
author_sort | Trojovský, Pavel |
collection | PubMed |
description | Stochastic-based optimization algorithms are effective approaches to addressing optimization challenges. In this article, a new optimization algorithm called the Election-Based Optimization Algorithm (EBOA) was developed that mimics the voting process to select the leader. The fundamental inspiration of EBOA was the voting process, the selection of the leader, and the impact of the public awareness level on the selection of the leader. The EBOA population is guided by the search space under the guidance of the elected leader. EBOA’s process is mathematically modeled in two phases: exploration and exploitation. The efficiency of EBOA has been investigated in solving thirty-three objective functions of a variety of unimodal, high-dimensional multimodal, fixed-dimensional multimodal, and CEC 2019 types. The implementation results of the EBOA on the objective functions show its high exploration ability in global search, its exploitation ability in local search, as well as the ability to strike the proper balance between global search and local search, which has led to the effective efficiency of the proposed EBOA approach in optimizing and providing appropriate solutions. Our analysis shows that EBOA provides an appropriate balance between exploration and exploitation and, therefore, has better and more competitive performance than the ten other algorithms to which it was compared. |
format | Online Article Text |
id | pubmed-9138015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91380152022-05-28 A new optimization algorithm based on mimicking the voting process for leader selection Trojovský, Pavel Dehghani, Mohammad PeerJ Comput Sci Algorithms and Analysis of Algorithms Stochastic-based optimization algorithms are effective approaches to addressing optimization challenges. In this article, a new optimization algorithm called the Election-Based Optimization Algorithm (EBOA) was developed that mimics the voting process to select the leader. The fundamental inspiration of EBOA was the voting process, the selection of the leader, and the impact of the public awareness level on the selection of the leader. The EBOA population is guided by the search space under the guidance of the elected leader. EBOA’s process is mathematically modeled in two phases: exploration and exploitation. The efficiency of EBOA has been investigated in solving thirty-three objective functions of a variety of unimodal, high-dimensional multimodal, fixed-dimensional multimodal, and CEC 2019 types. The implementation results of the EBOA on the objective functions show its high exploration ability in global search, its exploitation ability in local search, as well as the ability to strike the proper balance between global search and local search, which has led to the effective efficiency of the proposed EBOA approach in optimizing and providing appropriate solutions. Our analysis shows that EBOA provides an appropriate balance between exploration and exploitation and, therefore, has better and more competitive performance than the ten other algorithms to which it was compared. PeerJ Inc. 2022-05-13 /pmc/articles/PMC9138015/ /pubmed/35634108 http://dx.doi.org/10.7717/peerj-cs.976 Text en ©2022 Trojovský and Dehghani https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Trojovský, Pavel Dehghani, Mohammad A new optimization algorithm based on mimicking the voting process for leader selection |
title | A new optimization algorithm based on mimicking the voting process for leader selection |
title_full | A new optimization algorithm based on mimicking the voting process for leader selection |
title_fullStr | A new optimization algorithm based on mimicking the voting process for leader selection |
title_full_unstemmed | A new optimization algorithm based on mimicking the voting process for leader selection |
title_short | A new optimization algorithm based on mimicking the voting process for leader selection |
title_sort | new optimization algorithm based on mimicking the voting process for leader selection |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9138015/ https://www.ncbi.nlm.nih.gov/pubmed/35634108 http://dx.doi.org/10.7717/peerj-cs.976 |
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