Numerical Comparison of some Crossover in Genetic Algorithm for Two Dimensional Global Minimization Problem using C++

In this paper we simulate the comparison of numerical results of the different crossover method in genetics algorithm for solving global minimization problem. In this paper, the objective function is for 2 two variables function. The genetics algorithm is run using C++ program and implemented to sev...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2019-10, Vol.621 (1), p.12018
Main Authors: Johansyah, Muhamad Deni, Napitupulu, Herlina, Djauhari, Eddy, Sukono, Nahar, Julita
Format: Article
Language:English
Subjects:
Algorithms
Benchmarks
C++ (programming language)
Crossovers
Genetic algorithms
Genetics
Global optimization
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Summary:In this paper we simulate the comparison of numerical results of the different crossover method in genetics algorithm for solving global minimization problem. In this paper, the objective function is for 2 two variables function. The genetics algorithm is run using C++ program and implemented to several benchmark test functions of global optimization. The performance of each crossover method is analyse according to the numerical results, which show that certain crossover method is better for certain benchmark test function.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/621/1/012018