ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization
Özet
Heuristic based computational algorithms are densely being used in many different fields due to their advantages. When investigated carefully, chemical reactions possess efficient objects, states, process, and events that can be designed as a computational method en bloc. In this study, a novel computational method, which is more robust and have less parameters than that of used in the literature, is intended to be developed inspiring from types and occurring of chemical reactions. The proposed method is named as Artificial Chemical Reaction Optimization Algorithm, ACROA. Applications to multiple-sequence alignment, data mining, and benchmark functions have been performed so as to put forward the performance of developed computational method. (C) 2011 Elsevier Ltd. All rights reserved.
Anahtar Kelimeler
- WoS
- 340
- OpenAlex
- 420
Tam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Alatas, Bilal | |
| dc.date.accessioned | 2026-10-28T15:03:36.110960608Z | |
| dc.date.available | 2026-10-28T15:03:36.110960608Z | |
| dc.date.issued | 2011-09 | |
| dc.description.abstract | Heuristic based computational algorithms are densely being used in many different fields due to their advantages. When investigated carefully, chemical reactions possess efficient objects, states, process, and events that can be designed as a computational method en bloc. In this study, a novel computational method, which is more robust and have less parameters than that of used in the literature, is intended to be developed inspiring from types and occurring of chemical reactions. The proposed method is named as Artificial Chemical Reaction Optimization Algorithm, ACROA. Applications to multiple-sequence alignment, data mining, and benchmark functions have been performed so as to put forward the performance of developed computational method. (C) 2011 Elsevier Ltd. All rights reserved. | |
| dc.description.sponsorship | Turkish Scientific and Technical Research Council - TUBITAK [MAG-110M309] | |
| dc.identifier.doi | 10.1016/j.eswa.2011.04.126 | |
| dc.identifier.eissn | 1873-6793 | |
| dc.identifier.endpage | 13180 | |
| dc.identifier.issn | 0957-4174 | |
| dc.identifier.issue | 10 | |
| dc.identifier.startpage | 13170 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/munzur/4669 | |
| dc.identifier.volume | 38 | |
| dc.identifier.wos | WOS:000292169500127 | |
| dc.language.iso | en | |
| dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | |
| dc.relation.ispartof | EXPERT SYSTEMS WITH APPLICATIONS | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Heuristic optimization | |
| dc.subject | Computational method | |
| dc.subject | Chemical reaction | |
| dc.subject | Performance | |
| dc.subject.classification | Computer Science, Artificial Intelligence | |
| dc.subject.classification | Engineering, Electrical & Electronic | |
| dc.subject.classification | Operations Research & Management Science | |
| dc.subject.classification | Computer Science | |
| dc.subject.classification | Engineering | |
| dc.subject.other | PARTICLE SWARM OPTIMIZATION | |
| dc.subject.other | GENETIC ALGORITHM | |
| dc.subject.other | SEARCH | |
| dc.subject.other | COLONY | |
| dc.subject.other | SYSTEM | |
| dc.title | ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization | |
| dc.type | Article | |
| rdl.citation.openalex | 420 | |
| rdl.citation.wos | 340 | |
| rdl.oa.status | closed | |
| rdl.scopus.quartile | Q1 | |
| rdl.source.index | WOS | |
| rdl.wos.index | Science Citation Index Expanded (SCI-EXPANDED) |
