Using Simple Genetic Algorithm for a Hand Contour Classification: An Experimental Study

2020 ◽  
pp. 93-109
Author(s):  
Jaroslav Moravec
Keyword(s):  
Genetic Algorithm ◽  
Experimental Study ◽  
Simple Genetic Algorithm

scholarly journals A Multiple Mitosis Genetic Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 252
Author(s):  
K. Kamil ◽  
K.H Chong ◽  
H. Hashim ◽  
S.A. Shaaya
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Total Population ◽  
Global Optimum ◽  
Natural Process ◽  
Local Optimum ◽  
Simple Genetic Algorithm ◽  
Cell Reproduction ◽  
Solve Optimization Problem ◽  
High Diversity

<p>Genetic algorithm is a well-known metaheuristic method to solve optimization problem mimic the natural process of cell reproduction. Having great advantages on solving optimization problem makes this method popular among researchers to improve the performance of simple Genetic Algorithm and apply it in many areas. However, Genetic Algorithm has its own weakness of less diversity which cause premature convergence where the potential answer trapped in its local optimum.  This paper proposed a method Multiple Mitosis Genetic Algorithm to improve the performance of simple Genetic Algorithm to promote high diversity of high-quality individuals by having 3 different steps which are set multiplying factor before the crossover process, conduct multiple mitosis crossover and introduce mini loop in each generation. Results shows that the percentage of great quality individuals improve until 90 percent of total population to find the global optimum.</p>

scholarly journals Designing a competent simple genetic algorithm for search and optimization

2000 ◽  
Vol 36 (12) ◽  
pp. 3757-3761 ◽  
Author(s):  
Patrick Reed ◽  
Barbara Minsker ◽  
David E. Goldberg
Keyword(s):  
Genetic Algorithm ◽  
Simple Genetic Algorithm
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