Multicriteria conditional optimization based on genetic algorithms




multicriteria optimization, conditional optimization, genetic algorithms, repairing algorithm, SPEA2, Pareto optimization


This article takes on solving the problem of multicriteria conditional optimization. This problem is one of the most key tasks of the current time and has its application in many areas. Reuse of various existing algorithms for solving unconstrained optimization is proposed. Different methods of multicriteria unconditional optimization are reviewed. The advantages and disadvantages of each algorithm are analyzed. The algorithms modified to take into account the constraints. Additional algorithms of transition from solving an unconditional optimization problem to a conditional optimization problem are developed. A genetic algorithm SPEA2 was used to test the developed algorithms. Examples of solving the problem at hand using the aforementioned algorithms are presented. A comparative analysis of the final results was conducted.

Author Biographies

Victor M. Sineglazov, National Aviation University, Kyiv

Victor Sineglazov,

professor, Doctor of Technical Sciences, the head of the Department of Aviation Computer Integrated Technologies of National Aviation University, Kyiv, Ukraine.

Kirill D. Riazanovskiy, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Kirill Riazanovskiy,

a graduate student at the Department of Technical Cybernetics of the Faculty of Informatics and Computer Science of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine.

Olena I. Chumachenko, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Olena Chumachenko,

Doctor of Technical Sciences, an associate professor at the Department of Technical Cybernetics of the Faculty of Informatics and Computer Science of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine.


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Methods of optimization, optimum control and theory of games