Performance Comparisons of Optimization Algorithms
dc.authorscopusid | 57207467860 | |
dc.authorscopusid | 57194830856 | |
dc.authorscopusid | 6602929072 | |
dc.authorwosid | Karaduman, Mucahit/R-6853-2017 | |
dc.authorwosid | Karci, Ali/A-9604-2019 | |
dc.contributor.author | Inan, M. | |
dc.contributor.author | Karaduman, M. | |
dc.contributor.author | Karci, A. | |
dc.date.accessioned | 2025-05-10T17:01:57Z | |
dc.date.available | 2025-05-10T17:01:57Z | |
dc.date.issued | 2019 | |
dc.department | T.C. Van Yüzüncü Yıl Üniversitesi | en_US |
dc.department-temp | Inan M., Baskale Meslek Yuksekokulu, Bilgisayar Teknolojileri Bolumu, Yucuncu Yil Universitesi, Van, Turkey; Karaduman M., Arapgir Meslek Yuksekokulu, Bilgisayar Teknolojileri Bolumu, Inonu Universiyesi, Malatya, Turkey; Karci A., Muhendislik Fakultesi, Bilgisayar Muhendisligi, Inonu Universitesi, Malatya, Turkey | en_US |
dc.description.abstract | Optimization methods are applied to many different problems. While these methods do not guarantee a definite end result, they give a solution that is close to the best result in a reasonable time. Optimization methods are classified as physical, social, music, herd, chemistry, biology and hybrid methods when classified according to the sources they are influenced by. In this study, it is aimed to compare the 5 methods of swarm optimization algorithm methods under the same conditions and applying the same probing. Thus, it is possible to determine the method that obtains the best values in terms of result and speed, and gives the fastest result. For this purpose, cat swarm optimization, whale swarm optimization, cricket algorithm, crow search optimization and salp optimization methods have been determined. When the result obtained from the comparison is evaluated, the best calculation time of the calculations for all functions is done with crow search optimization, the best results are obtained with whale swarm optimization for Ackley, salp optimization methods for Bukin N 6 and crow search optimization for Rastrigin. © 2018 IEEE. | en_US |
dc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
dc.identifier.doi | 10.1109/IDAP.2018.8620752 | |
dc.identifier.isbn | 9781538668788 | |
dc.identifier.scopus | 2-s2.0-85062569913 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.uri | https://doi.org/10.1109/IDAP.2018.8620752 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14720/5352 | |
dc.identifier.wos | WOS:000458717400033 | |
dc.identifier.wosquality | N/A | |
dc.language.iso | tr | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | 2018 International Conference on Artificial Intelligence and Data Processing, IDAP 2018 -- 2018 International Conference on Artificial Intelligence and Data Processing, IDAP 2018 -- 28 September 2018 through 30 September 2018 -- Malatya -- 144523 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Benchmarking Functions | en_US |
dc.subject | Bso | en_US |
dc.subject | Cbo | en_US |
dc.subject | Kao | en_US |
dc.subject | Kso | en_US |
dc.subject | Optimization | en_US |
dc.subject | Ssa | en_US |
dc.title | Performance Comparisons of Optimization Algorithms | en_US |
dc.type | Conference Object | en_US |