Talk · AIP conference proceedings · January 1, 2024
Genetic algorithm application technology in multi-parameter optimization problems
Akmal Akhatov, Fayzullo Makhmadiyarovich Nazarov, Mekhriddin Nurmamatov, Shokhrukh Sariyev
Abstract
Genetic algorithms (GA) are optimization techniques inspired by the principles of natural selection and genetics. GA is widely used in various fields to solve complex optimization and search problems. In this study, the general view of genetic algorithms, their main concepts, components, and working processes were reviewed. Basic principles of population, selection, crossover and mutations are mentioned. In this study, the mathematical process of creating existing solutions of the object is explained and the suitability is evaluated and they are improved by successive approximation to the existing solution. Population numbers, selection strategies, crossover and mutation rates of GAs were examined. Strengths, limitations, and survival of the fittest and genetic crossover and mutation principles of GAs are used to design and develop solutions to the problem. GA uses crossover, mutation, selection and population mechanisms to reach the optimal solution.
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