American Journal of Modeling and Optimization
ISSN (Print): 2333-1143 ISSN (Online): 2333-1267 Website: http://www.sciepub.com/journal/ajmo Editor-in-chief: Dr Anil Kumar Gupta
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American Journal of Modeling and Optimization. 2015, 3(3), 56-67
DOI: 10.12691/ajmo-3-3-1
Open AccessArticle

Simulation and Optimal Decision Making the Design of Technical Systems

Yury K. MASHUNIN1, and Konstantin Yu. MASHUNIN1

1Far Eastern Federal University, Vladivostok, Russia

Pub. Date: October 08, 2015

Cite this paper:
Yury K. MASHUNIN and 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

Abstract

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.

Keywords:
modeling technical systems vector optimization optimum decision-making

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References:

[1]  Krasnoshchekov, P. S., Morozov, V. V., Popov, N. M. and Fedorov, V. V., “Hierarchical design schemes and decompositional numerical methods”, Journal of Comput. Syst. Sci. Int. Vol. 40, No. 5, 2001, pp.754-763.
 
[2]  Podinovskii, V. V. “Analysis of Multicriteria Choice Problems by Methods of the Theory of Criteria Importance, Based on Computer Systems of Decision_Making Support,” Comput. Syst. Sci. Int. 47, 221, 2008.
 
[3]  Lotov, A. V., Kamenev, G. K., and Berezkin, V. E., “Approximation and visualization of the Pareto frontier for nonconvex multi_objective problems,” Dokl. Akad. Nauk 386, 2002, 738-741.
 
[4]  Mashunin, Yu. K, Methods and Models of Vector Optimization, Nauka, Moscow, 1986, 146 p. (in Russian).
 
[5]  Mashunin, Yu. K., and Levitskii, V. L., Methods of Vector Optimization in Analysis and Synthesis of Engineering Systems. Monograph. DVGAEU, Vladivostok, 1996. 131 p. (in Russian).
 
[6]  Mashunin, Yu. K. “Solving composition and decomposition problems of synthesis of complex engineering systems by vector optimization methods”. Comput. Syst. Sci. Int. 38, 421-426, 1999.
 
[7]  Mashunin K. Yu., and Mashunin Yu. K. “Simulation Engineering Systems under Uncertainty and Optimal Descision Making”. Journal of Comput. Syst. Sci. Int. Vol. 52. No. 4. 2013. 519-534.
 
[8]  Mashunin Yu. K. Control Theory. The mathematical apparatus of management of the economy. Logos. Moscow. 2013, 448 p. (in Russian).
 
[9]  Mashunin Yu. K., and Mashunin K. Yu. “Modeling of technical systems on the basis of vector optimization (1. At equivalent criteria)”. International Journal of Engineering Sciences & Research Technology. 3(9): September, 2014. P. 84-96.
 
[10]  Mashunin Yu. K., and Mashunin K. Yu. “Modeling of technical systems on the basis of vector optimization (2. with a Criterion Priority)”. International Journal of Engineering Sciences & Research Technology. 3(10): October, 2014. P. 224-240.
 
[11]  Mashunin Yu.K. “Vector optimization a mathematical apparatus of system optimal decision-making in economic and technical systems (1. Method)”. Oxford Review of Education and science. Oxford University Press, 2015. 1(9). P. 187-196.
 
[12]  Mashunin Yu.K. “Vector optimization a mathematical apparatus of system optimal decision-making in economic and technical systems (2. Practic)”. Oxford Review of Education and science. Oxford University Press, 2015. 1(9). P.197-210.
 
[13]  Torgashov A. Yu., Krivosheev V. P., Mashunin Yu. K., and Holland Ch. D., “Calculation and multiobjective optimization of static modes of mass_exchange processes by the example of absorption in gas separation,” Izv. Vyssh.Uchebn. Zaved., Neft’ Gaz, No. 3, 82-86. 2001.
 
[14]  Ketkov Yu. L., Ketkov A. Yu., and Shul’ts M. M., MATLAB 6.x.: Numerical Programming. BKhV_Peterburg, St. Petersburg, 2004. 672 p. (in Russian).
 
[15]  Keeney, R. L. and Raiffa, H. Decisions with Multiple Objectives–Preferences and Value Tradeoffs (Wiley, New York, 1976; Radio i svyaz’, Moscow, 1981).
 
[16]  Balali, V., Zahraie, B., and Roozbahani, A. “Integration of ELECTRE III and PROMETHEE II Decision Making Methods with Interval Approach: Application in Selection of Appropriate Structural Systems.”ASCE Journal of Computing in Civil Engineering, 28(2), 2012. 297-314.
 
[17]  Johannes J. Vector Optimization: Theory, Applications, and Extensions. Berlin, Heidelberg, New York: Springer-Verlag, 2010. 460 p.
 
[18]  Ansari Q., and Jen-Chih Y. Recent Developments in Vector Optimization. Heidelberg, Dordrecht, London, New York: Springer 2010. 550 p.
 
[19]  Hirotaka N., Yeboon Y., and Min Y. Sequential Approximate Multiobjective Optimization Using Computational Intelligence. Berlin, Heidelberg: Springer-Verlag, 2009. 197 p.
 
[20]  Shankar R. Decision Making in the Manufacturing Environment: Using Graft Theory and fuzzy Multiple Attribute Decision Making Methods. Springer-Verlag, 2007. 373 p.
 
[21]  Cooke T., Lingard H., and Blismas N. The development end evaluation of a Decision Support Tool for Рealth and safety in Construction Design // Engineering, Construction and Architectural Management. V. 15. № 4. 2008. P. 336-351.