Method of converting a set of possible solutions in the theory of decision-making

Authors

DOI:

https://doi.org/10.15587/2313-8416.2017.118284

Keywords:

decision theory, multi-criteria problem, set of possible solutions, convex hull

Abstract

The problem of multi-criteria choice is considered in the paper, which are first reduced to single-criterion and then to the linear programming problem. For the effective solution of the problem provides a method of converting a set of possible solutions (the corresponding domain of admissible solutions) by eliminating from consideration deliberately unpromising alternatives with the opportunity to further their directional search. Numerical results of algorithm work are given in the presence of three to five criteria

Author Biographies

Micola Pogozhikh, Kharkiv State University of Food Technology and Trade Klochkivska str., 333, Kharkiv, Ukraine, 61051

Doctor of Technical Sciences, Professor, Head of Department

Department of physical and mathematical and engineering-technical disciplines

Marina Sofronova, Kharkiv State University of Food Technology and Trade Klochkivska str., 333, Kharkiv, Ukraine, 61051

PhD, Associate Professor

Department of physical and mathematical and engineering-technical disciplines

Dmitry Panasenko, National Technical University «Kharkiv Politechnic Institute» Kyrpychova str., 2, Kharkiv, Ukraine, 61002

Assistant

Department of Computer and Radioelectronic Systems of Testing and Diagnostics

References

Poltavskiy, A. В., Semenov, S. S., Burba, A. A. (2014). Metody prinyatiya resheniy pri razrabotke obyektov slozhnykh tekhnicheskikh sistem [Methods of making the devlopment of objects complex technical systems]. Dual technologies, 3 (68), 38–46.

Optner, S. A. (1969). Sistemnyy analiz dlya resheniya delovykh i promyshlennykh problem [System analysis for solving business and industrial problems]. Moscow: Soviet radio, 216.

Samarskyi, A. A., Mihailov, A. P. (2001) Matematicheskoye modelirovaniye: Idei. Metody. Primery [Mathematical Modeling: Ideas. Methods. Examples]. Moscow: Fizmatlit, 320.

Urubkov, A. R., Fedotov, I. V. (2011). Metody i modeli optimizatsii upravlencheskikh resheniy [Methods and models for optimizing management decisions]. Moscow: Delo ANKH, 240.

Churakov, E. P. (2004). Matematicheskiye metody obrabotki eksperimental'nykh dannykh v ekonomike [Mathematical methods for processing experimental data in the economy]. Moscow: Finance and Statistics, 240.

Geoffrion, A. M., Dyer, J. S., Feinberg, A. (1972). An Interactive Approach for Multi-Criterion Optimization, with an Application to the Operation of an Academic Department. Management Science, 19 (4), 357–368. doi: 10.1287/mnsc.19.4.357

Rosenberg, R. (1967). Simulation of genetic populations with biochemical properties. Ann Arbor: University of Michigan.

Nogin, V. D. (2008). Problema suzheniya mnozhestva Pareto: podkhody k resheniyu [The problem of narrowing the Pareto set: approaches to solving]. Artificial Intelligence and Decision Making, 1, 98–112.

Sobol, S. M., Statnikov, R. B. (2006). Vybor optimal'nykh parametrov v zadachakh so mnogimi kriteriyami [The choice of optimal parameters in problems with many criteria]. Moscow: Drofa, 175.

McMullen, P., Shephard, G. (1971). Convex Polytopes and the Upper Bound Conjecture. Cambridge: Cambridge University Press.

Gil, N. I., Sofronova, M. S. (2009). Ob odnom podkhode k postroyeniyu vypukloy obolochki konechnogo mnozhestva tochek v Rn [On an approach to the construction of the convex hull of a finite set of points in Rn ]. Artificial intelligence, 4, 30–36.

Published

2017-12-30

Issue

Section

Technical Sciences