Study of Crossover and Mutation Operators Control in Real Coded Genetic Algorithm Applying to Solve an Optimization Task
Proceedings of 14th International Conference on Soft Computing MENDEL 2008 2008
Irina Provorova, Ludmila Aleksejeva

The paper discusses the possibility to manage search direction in genetic algorithm crossover and mutation operators using “Depository of Weak Individuals’ Fitness Values”. In order to control crossover and mutation, it was decided to observe the individuals that take part in those operators. All offsprings that are produced during crossover operator run will be compared with the individuals that are their predecessors – worse individual fitness value will be kept in the “Depository of Weak Individuals’ Fitness Values” during all generations. And mutation operator consists of several steps – individual’s mutation will be repeated until better offspring is found. If better solution is found, then the individual selected for mutation will be kept during all generations in the “Depository of Weak Individuals Fitness Values”.


Keywords
real coded genetic algorithm, crossover and mutation operators, optimization task

Provorova I., Aleksejeva L. Study of Crossover and Mutation Operators Control in Real Coded Genetic Algorithm Applying to Solve an Optimization Task // Proceedings of 14th International Conference on Soft Computing MENDEL 2008, Czech Republic, Brno, 18.-20. June, 2008. - pp 65-70.

Publication language
English (en)
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