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Exact(7)
In this GA, arithmetic crossover and random mutation are applied to generate new offsprings.
In a standard GA, solution hypotheses are represented as code strings; this is also called a genotype where genetic operators such as crossover and mutation are applied.
The operators of selection, crossover and mutation are applied to the initial population, and it stops when the Genetic Algorithm converges or reaches the maximum evolution step.
The natural evolutional processes of reproduction, selection, crossover, and mutation are applied using probability rules to evolve the new and better generations.
Three biased selection schemes for reproduction; four for recombination and three for mutation are applied in it and a new selection scheme for replacement is approached.
At each iteration (namely, generation), the genetic operators of crossover and mutation are applied on selected chromosomes with probabilities and, respectively, in order to generate new solutions belonging to the search space.
Similar(53)
In the present case, mutation is applied if no improvement is observed in five iterations.
Further to create a new population, operations like reproduction, crossover and mutation were applied consecutively.
Non-uniform mutation is applied to the membership functions which are represented as real numbers.
Uniform mutation is applied to the rule set which is represented as discrete numbers.
After mutation is applied to a selection of the child solutions, the newly created solutions are inserted back into the gene pool.
More suggestions(15)
mutation are used
mutation are denoted
mutation are associated
mutation are provided
mutation are chosen
mutation are inherited
mutation are warranted
mutation are employed
mutation are shown
mutation are imagined
mutation are sewn
mutation are explained
mutation are termed
mutation are reported
mutation are designed
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