Methods of Optimization and Systems Analysis for Problems of Transcomputational Complexity

Nonfiction, Science & Nature, Mathematics, Applied, Computers
Cover of the book Methods of Optimization and Systems Analysis for Problems of Transcomputational Complexity by Ivan V. Sergienko, Springer New York
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Author: Ivan V. Sergienko ISBN: 9781461442110
Publisher: Springer New York Publication: July 27, 2012
Imprint: Springer Language: English
Author: Ivan V. Sergienko
ISBN: 9781461442110
Publisher: Springer New York
Publication: July 27, 2012
Imprint: Springer
Language: English

This work presents lines of investigation and scientific achievements of the Ukrainian school of optimization theory and adjacent disciplines. These include the development of approaches to mathematical theories, methodologies, methods, and application systems for the solution of applied problems in economy, finances, energy saving, agriculture, biology, genetics, environmental protection, hardware and software engineering, information protection, decision making, pattern recognition, self-adapting control of complicated objects, personnel training, etc. The methods developed include sequential analysis of variants, nondifferential optimization, stochastic optimization, discrete optimization, mathematical modeling, econometric modeling, solution of extremum problems on graphs, construction of discrete images and combinatorial recognition, etc. Some of these methods became well known in the world's mathematical community and are now known as classic methods.

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This work presents lines of investigation and scientific achievements of the Ukrainian school of optimization theory and adjacent disciplines. These include the development of approaches to mathematical theories, methodologies, methods, and application systems for the solution of applied problems in economy, finances, energy saving, agriculture, biology, genetics, environmental protection, hardware and software engineering, information protection, decision making, pattern recognition, self-adapting control of complicated objects, personnel training, etc. The methods developed include sequential analysis of variants, nondifferential optimization, stochastic optimization, discrete optimization, mathematical modeling, econometric modeling, solution of extremum problems on graphs, construction of discrete images and combinatorial recognition, etc. Some of these methods became well known in the world's mathematical community and are now known as classic methods.

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