Abstract
In article discusses issues for solving optimization problems based on the use of genetic algorithms. Nowadays, the genetic algorithms for solving various problems. This includes the shortest path search, approximation, data filtering and others. In particular, data is being examined regarding the use of a genetic algorithm to solve problems of optimizing the modes of electric power systems. Imagine an algorithm for developing the development of mathematical models, which includes developing the structure of the chromosome, creating a started population, creating a directing force for the population, etc.
Highlights
Genetic algorithms are currently very popular ways to solve optimization problems
2) Genetic algorithm for optimization of modes of power systems taking into ac-count the functional constraints in the form of inequalities by exponential form of penalty function has a reliable convergence of an iterative calculation process
3) The proposed algorithm of taking into account of functional constraints in opti-mization by genetic algorithms can be effectively used for optimal planning of short-term modes of power systems
Summary
Genetic algorithms are currently very popular ways to solve optimization problems. They are based on the use of evolutionary principles to find the optimal solution. The very idea seems quite intriguing and curious to put it into practice, and numerous positive results only stir up interest from researchers. A small change in one of them can lead to an unexpected improvement in the result. The use of genetic algorithms is useful only in cases where for this problem there is no suitable special solution algorithm. These algorithms are based on the principles of natural selection by
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