A3-ARTIFICIAL ATOM ALGORITHM: A NEW META-HEURISTIC COMPUTATIONAL INTELLIGENCE ALGORITHM INSPIRED BY CHEMICAL PROCESSES

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dc.authoridKarci, Ali/0000-0002-8489-8617;
dc.authorwosidKarci, Ali/AAG-5337-2019
dc.authorwosidKARCI, Ali/A-9604-2019
dc.contributor.authorKarci, Ali
dc.date.accessioned2024-08-04T20:53:11Z
dc.date.available2024-08-04T20:53:11Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.description.abstractMost of the meta-heuristic algorithms are based on the natural processes. They were inspired by physical, biological, social, chemical, social-biological, biological-geography, music, and hybrid processes. In this paper, we propose a new meta-heuristic algorithm based on the chemical process of compound formation. In order to form compound, some electrons are removed from some elements, and some electrons are attached to some elements. The formed bond is called the ionic bond. In another case, at least two elements share at least one electron in common, and the constructed bond is called the covalent bond. Proposed algorithm based on compound formation process in this paper is a population based algorithm, and population consists of candidate solutions-subject to evolution for convergence to optimal/near optimal solutions. These solutions were called atoms, and the attributes of each solution were called electrons. The set of solutions constructs Atom Set where initially, atoms are constructed randomly. Then there are two operators in the proposed algorithm to make candidate solutions be better. So, this process is applied to solutions until desired solution is obtained.The formation of covalent bond in chemistry is mimicked as covalent bond where better attribute value is shared between at least two atoms. The ionic bond process is mimicked as ionic bond, and some attribute values of each atom reassigned randomly. The obtained algorithm was called as Artificial Atom Algorithm (A3). It is superior with respect to other natural-inspired metaheuristic algorithms, since it is applied once and global optimum or near-global optimum point was obtained. On contrary, other meta-heuristic algorithms are applied more than once, and the better obtained result is selected as a result of experiment. Another important point is that this algorithm does not have more algorithm parameters. There are just ionic rate (covalent rate) parameter (ionic rate +covalent rate = 1).en_US
dc.identifier.endpage140en_US
dc.identifier.issn1683-3511
dc.identifier.issn1683-6154
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85142331836en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage119en_US
dc.identifier.urihttps://hdl.handle.net/11616/101005
dc.identifier.volume17en_US
dc.identifier.wosWOS:000448677200001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMinistry Communications & High Technologies Republic Azerbaijanen_US
dc.relation.ispartofApplied and Computational Mathematicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMeta-heuristic Methodsen_US
dc.subjectEvolutionary Computationen_US
dc.subjectGenetic Algorithmsen_US
dc.subjectNature-Inspired Methodsen_US
dc.titleA3-ARTIFICIAL ATOM ALGORITHM: A NEW META-HEURISTIC COMPUTATIONAL INTELLIGENCE ALGORITHM INSPIRED BY CHEMICAL PROCESSESen_US
dc.typeArticleen_US

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