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This simple cycle is the basic step in the GA because repeating this procedure and according to supposed criteria, the best answer for optimization problem would be derived.
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On the other hand, in the last twenty years, a genetic algorithm GA) is attracted as one method which gives us suitable answers for search, optimization and machine learning problems.
On the other hand, in the last twenty years, GA is attracted as one method which gives us optimal answers for global search, optimization and machine learning problems.
Presently computerized optimization technique based on response surface methodology (RSM) is used for optimization purpose.
Pseudo-Boolean optimization was used for optimization.
The algorithm is just a tool for optimization.
Chances are there's some room for optimization.
It is a classic problem in computer science and is used as a benchmark test for optimization algorithms.
No strict constraints are applied for optimization.
Corresponding constraints are used for optimization.
Evolutionary algorithms for numerical optimization with a good exploratory behavior should be used for optimization.
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