Abstract
The paper deals with practical issues of using the apparatus of genetic algorithms as one of the directions of optimization based on heuristic optimization methods. The adequacy of the application of genetic algorithms in the problem of two-dimensional optimal placement of a bit sequence in a bounded two-dimensonal space is shown. The probabilistic mechanism of application of the mutational genetic operator is used.
Highlights
Genetic algorithms are adaptive search methods used to solve functional optimization problems [1]
This method differs from most other optimization algorithms, which operate with only one solution, improving it [3]
The methods of evolutionary search look relatively new: genetic algorithms and methods of genetic programming. These methods successfully combine the advantages of heuristic methods, as well as ways to get out of local extremes
Summary
Genetic algorithms are adaptive search methods used to solve functional optimization problems [1]. Genetic algorithms operate on a set of individuals (population), which are strings that encode one of the solutions of the problem [2]. This method differs from most other optimization algorithms, which operate with only one solution, improving it [3].
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