Study on Selection Methods of Parents and Crossover in Genetic Algorithm
K. Santhi, V. Vinodhini
Abstract
Open-access reader
K. Santhi, V. Vinodhini
Abstract
Open-access reader
Genetic Algorithms are the population based search and optimization technique that mimic the process of Genetic and Natural Evolution. Genetic algorithms are very effective way of finding an Optimized solution to a complex problem. Performance of genetic algorithms mainly depends on various factors such as selection of efficient parents and type of genetic operators which involve crossover and mutation operators etc. This paper will help the people to acquire the knowledge about various strategies of selecting parents and description about standard crossover operators.
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Genetic Algorithms are the population based search and optimization technique that mimic the process of Genetic and Natural Evolution. Genetic algorithms are very effective way of finding an Optimized solution to a complex problem. Performance of genetic algorithms mainly depends on various factors such as selection of efficient parents and type of genetic operators which involve crossover and mutation operators etc. This paper will help the people to acquire the knowledge about various strategies of selecting parents and description about standard crossover operators.
Key concepts: Crossover, Genetic representation, Selection (genetic algorithm), Genetic algorithm, Quality control and genetic algorithms, Mutation, Computer science, Genetic operator