Key words
simulation modeling, genetic algorithm, intelligence calculations, population, selection, mutation, inheritance, next generation.
articles
Authors:
Emelyanov A., Bulygina O. V., Emelyanova N., Vlasova E. Published in
№ 6(72)
29 december 2017 year
Rubric: Actor modeling
Rubric: Actor modeling
Complex simulation using genetic algorithms
Genetic algorithms are used in various forms to solve scientific and technical problems. They are
used to create computational structures. In machine learning, they are used in the design of neural networks
or in the control of robots. They are also used to model development in different subject areas,
including social, economic and political systems. It is possible and heuristic-mathematical application
of genetic algorithms for multiparameter functions optimization. Most real problems can be formulated
as the search for the optimal value, where such a value is a complex function, depending on
certain input parameters. In cases where the exact optimum is not needed, a solution can be any value
that is better than a given value. Then the genetic algorithm is an acceptable method for finding «acceptable
» values.
The strength of the genetic algorithm lies in its ability to manipulate many parameters simultaneously;
this is used in different projects, including even aircraft design. However, the formal, purely
mathematical application of such algorithms, without taking into account time characteristics, dynamics
and other features of real processes, where they are applied, can either not give a rational effect,
or lead to an erroneous decision. One of the ways of linking the appropriate models of decision support
to dynamics is a complex modeling of the studied processes on the basis of simulation modeling
using genetically-based algorithms.
The author:
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The author:
Bulygina O. V.
Degree:
Cand. Sci. (Econ.), Associate Professor, department of Information Technology in Economics and Management, the Branch of National Research University MPEI in Smolensk
Location:
Smolensk
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The author:
Vlasova E.
Degree:
Leading Researcher, Moscow University for Industry and Finance «Synergy»
Location:
Moscow
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