PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS

Alpha Male Genetic Algorithms are sexist and population based optimization tools that mimic the swarm behavior of animals. The algorithm consists on a socially partitioned population of individuals where the partitions are formed by sexual selection of females. In this paper, we suggest to use Linea...

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Main Authors: Mehmet Hakan SATMAN, Emre AKADAL
Format: Article
Language:deu
Published: Trakya University 2019-06-01
Series:Trakya Üniversitesi Sosyal Bilimler Dergisi
Subjects:
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author Mehmet Hakan SATMAN
Emre AKADAL
author_facet Mehmet Hakan SATMAN
Emre AKADAL
author_sort Mehmet Hakan SATMAN
collection DOAJ
description Alpha Male Genetic Algorithms are sexist and population based optimization tools that mimic the swarm behavior of animals. The algorithm consists on a socially partitioned population of individuals where the partitions are formed by sexual selection of females. In this paper, we suggest to use Linear Crossover and Hooke-Jeeves method for crossover and hybridization operators of Alpha Male Genetic Algorithms, respectively. We perform a simulation study using a set of well-known test functions to reveal performance differences between the specialized algorithm and some other well-known optimization techniques including Genetic Algorithms, Differential Evolution, Particle Swarm Optimization, and Artificial Bee Colony Optimization. Simulation results show that the specialized algorithm outperforms its counterparts in most of the cases.
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spelling doaj.art-5e938e2cd3014c5886782f9bc5c634b62023-02-15T16:14:47ZdeuTrakya UniversityTrakya Üniversitesi Sosyal Bilimler Dergisi1305-77662587-24512019-06-01211558210.26468/trakyasobed.452095PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMSMehmet Hakan SATMAN0Emre AKADAL1İstanbul Universityİstanbul UniversityAlpha Male Genetic Algorithms are sexist and population based optimization tools that mimic the swarm behavior of animals. The algorithm consists on a socially partitioned population of individuals where the partitions are formed by sexual selection of females. In this paper, we suggest to use Linear Crossover and Hooke-Jeeves method for crossover and hybridization operators of Alpha Male Genetic Algorithms, respectively. We perform a simulation study using a set of well-known test functions to reveal performance differences between the specialized algorithm and some other well-known optimization techniques including Genetic Algorithms, Differential Evolution, Particle Swarm Optimization, and Artificial Bee Colony Optimization. Simulation results show that the specialized algorithm outperforms its counterparts in most of the cases.OptimizationEvolutionary algorithmsSimulations.
spellingShingle Mehmet Hakan SATMAN
Emre AKADAL
PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS
Trakya Üniversitesi Sosyal Bilimler Dergisi
Optimization
Evolutionary algorithms
Simulations.
title PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS
title_full PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS
title_fullStr PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS
title_full_unstemmed PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS
title_short PERFORMANCE COMPARISON OF THE SPECIALIZED ALPHA MALE GENETIC ALGORITHM WITH SOME EVOLUTIONARY ALGORITHMS
title_sort performance comparison of the specialized alpha male genetic algorithm with some evolutionary algorithms
topic Optimization
Evolutionary algorithms
Simulations.
work_keys_str_mv AT mehmethakansatman performancecomparisonofthespecializedalphamalegeneticalgorithmwithsomeevolutionaryalgorithms
AT emreakadal performancecomparisonofthespecializedalphamalegeneticalgorithmwithsomeevolutionaryalgorithms