A new optimization algorithm based on mimicking the voting process for leader selection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F22%3A50019195" target="_blank" >RIV/62690094:18470/22:50019195 - isvavai.cz</a>

Result on the web

<a href="https://peerj.com/articles/cs-976/" target="_blank" >https://peerj.com/articles/cs-976/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7717/peerj-cs.976" target="_blank" >10.7717/peerj-cs.976</a>

Result language

angličtina

Original language name

A new optimization algorithm based on mimicking the voting process for leader selection

Original language 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&apos;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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10102 - Applied mathematics

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

PeerJ Computer Science

ISSN

2376-5992

e-ISSN

2376-5992

Volume of the periodical

8

Issue of the periodical within the volume

MAY

Country of publishing house

GB - UNITED KINGDOM

Number of pages

40

Pages from-to

"Article Number: e976"

UT code for WoS article

000799792100002

EID of the result in the Scopus database

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