TSA: Tree-seed algorithm for continuous optimization

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dc.contributor.authorKiran, Mustafa Servet
dc.date.accessioned2020-03-26T19:07:48Z
dc.date.available2020-03-26T19:07:48Z
dc.date.issued2015
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis paper presents a new intelligent optimizer based on the relation between trees and their seeds for continuous optimization. The new method is in the field of heuristic and population-based search. The location of trees and seeds on n-dimensional search space corresponds with the possible solution of an optimization problem. One or more seeds are produced from the trees and the better seed locations are replaced with the locations of trees. While the new locations for seeds are produced, either the best solution or another tree location is considered with the tree location. This consideration is performed by using a control parameter named as search tendency (ST), and this process is executed for a pre-defined number of iterations. These mechanisms provide to balance exploitation and exploration capabilities of the proposed approach. In the experimental studies, the effects of control parameters on the performance of the method are firstly examined on 5 well-known basic numeric functions. The performance of the proposed method is also investigated on the 24 benchmark functions with 2, 3, 4, 5 dimensions and multilevel thresholding problems. The obtained results are also compared with the results of state-of-art methods such as artificial bee colony (ABC) algorithm, particle swarm optimization (PSO), harmony search (HS) algorithm, firefly algorithm (FA) and the bat algorithm (BA). Experimental results show that the proposed method named as TSA is better than the state-of-art methods in most cases on numeric function optimization and is an alternative optimization method for solving multilevel thresholding problem. (C) 2015 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2015.04.055en_US
dc.identifier.endpage6698en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue19en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage6686en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2015.04.055
dc.identifier.urihttps://hdl.handle.net/20.500.12395/32713
dc.identifier.volume42en_US
dc.identifier.wosWOS:000356735100017en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectHeuristic searchen_US
dc.subjectTree and seeden_US
dc.subjectNumeric optimizationen_US
dc.subjectMultilevel thresholdingen_US
dc.titleTSA: Tree-seed algorithm for continuous optimizationen_US
dc.typeArticleen_US

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