Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/4797
Title: Trait-based heterogeneous populations plus (TbHP+) genetic algorithm
Authors: Tayfur, Gökmen
Sevil, Hakkı Erhan
Gezgin, Erkin
Özdemir, Serhan
Keywords: Character fitness
Genetic algorithm
Heterogeneous population
Immunity
Instinct
Memory concept
Issue Date: Feb-2009
Publisher: Elsevier Ltd.
Source: Tayfur, G., Sevil, E. H., Gezgin, E., and Özdemir, S. (2009). Trait-based heterogeneous populations plus (TbHP+) genetic algorithm. Mathematical and Computer Modelling, 49(3-4), 709-720. doi:10.1016/j.mcm.2008.08.016
Abstract: This study developed a variant of genetic algorithm (GA) model called the trait-based heterogeneous populations plus (TbHP+). The developed TbHP+ model employs a memory concept in the form of immunity and instinct to provide the populations with a more efficient guidance. Also, it has an ability to vary the number of individuals during the search process, thus allowing an automatic determination of the size of the population based on the individual qualities such as character fitness and credit for immunity. The algorithm was tested against the classical GA model in convergence and minimum error performance. For this purpose, 5 different mathematical functions from the literature were employed. The selected functions have different topological characteristics, ranging from simple convex curves with 2 variables to complex trigonometric ones having several hilly shapes with more than 2 variables. The developed model and the classical GA model were applied to finding the global minima of the functions. The comparison of the results revealed that the developed TbHP+ model outperformed the classical GA in faster convergence and minimum errors, which may be explained by the adaptive nature of the new paradigm.
URI: http://dx.doi.org/10.1016/j.mcm.2008.08.016
http://hdl.handle.net/11147/4797
ISSN: 0895-7177
0895-7177
Appears in Collections:Civil Engineering / İnşaat Mühendisliği
Mechanical Engineering / Makina Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File Description SizeFormat 
4797.pdfMakale3.93 MBAdobe PDFThumbnail
View/Open
Show full item record

CORE Recommender

SCOPUSTM   
Citations

1
checked on Nov 27, 2021

WEB OF SCIENCETM
Citations

1
checked on Nov 27, 2021

Page view(s)

32
checked on Nov 28, 2021

Download(s)

22
checked on Nov 28, 2021

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.