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Johannes J. Vector Optimization: Theory, Applications, and Extensions. Berlin, Heidelberg, New York: Springer-Verlag, 2010. 460 p.

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Simulation and Optimal Decision Making the Design of Technical Systems

1Far Eastern Federal University, Vladivostok, Russia

American Journal of Modeling and Optimization. 2015, Vol. 3 No. 3, 56-67
DOI: 10.12691/ajmo-3-3-1
Copyright © 2015 Science and Education Publishing

Cite this paper:
Yury K. MASHUNIN, Konstantin Yu. MASHUNIN. Simulation and Optimal Decision Making the Design of Technical Systems. American Journal of Modeling and Optimization. 2015; 3(3):56-67. doi: 10.12691/ajmo-3-3-1.

Correspondence to: Yury  K. MASHUNIN, Far Eastern Federal University, Vladivostok, Russia. Email:


The paper presents a methodology for modeling and optimal decision-making in the design of the technical systems. The model is formed as a vector problem of mathematical programming. The model is intended to define the parameters of the technical system, in which the technical characteristics (criteria) are optimal. Mathematical model of the technical system is carried out in conditions of certainty (functional dependence of each characteristic and restrictions on parameters is known) and under conditions of uncertainty (there is not sufficient information on the characteristics of each of the functional dependence of the parameters). Conditions of uncertainty will be transformed to definiteness conditions, using methods of the regression analysis. The received to problems vector is solved on the basis of normalization of criteria and the principle of the guaranteed result. As a result of the decision received the optimum decision (the guaranteed result). The modeling methodology in the conditions of definiteness and uncertainty is illustrated on a numerical example of model of technical system, in the form of a vector problem of nonlinear programming with four criteria.