Abstract
The article considers the problem of selecting priority areas in research and development based on processing expert information used as a basis for the information computing system—an automated expert evaluation system. The resulting ordering of independent innovative projects takes into account the Kemeny median approach for preference vectors and the method for minimizing the sum of their ranks. It is proposed to develop the system in the form of a resource method for selecting priority areas. The probability distribution function of the technical success of a project in this method is described by the Weibull distribution. A mathematical model is developed to maximize the feasibility of a portfolio of independent projects. The feasibility is unstable if the source data are inaccurate. An effective method is recommended for solving the formulated problem of selecting a portfolio of priority (ongoing) innovative projects. A solution is proposed to the optimization problem of determining the priority of their financing.
Similar content being viewed by others
REFERENCES
Yu. N. Ivanov and V. V. Tokarev, “Formalized approach to the evaluation of new technologies,” in System Research. Methodological Problems (Nauka, Moscow, 1984) [in Russian].
Yu. N. Ivanov and V. V. Tokarev, Theoretical Economics: Range Evaluations of Innovations by Balance Models (LENAND, Moscow, 2015) [in Russian].
S. V. Dubovskii, “Scientific and technical progress in global modeling,” in System Research. Methodological Problems (Nauka, Moscow, 1988) [in Russian].
Foster, R. (1986). Innovation: The Attacker’s Advantage. New York: Free Press.
M. V. Kazantsev, Evaluation of the Directions of STP in the Methodology of National Economic Planning (Novosibirsk, 1989) [in Russian].
V. A. Glotov and V. V. Pavel’ev, Vector Stratification (Nauka, Moscow, 1984) [in Russian].
V. A. Pokrovskii, Increase Research and Development Efficiency (Nauka, Moscow, 1987) [in Russian].
L. I. Yakobson, Public Sector Economics: Fundamentals of Public Finance Theory (Aspekt Press, Moscow, 1996) [in Russian].
A. E. Boardman, D. H. Greenberg, and A. R. Vining, Cost-Benefit Analysis: Concepts and Practice, 3rd ed. (Prentice-Hall, Pearson, Upper Saddle River, 2006).
O. I. Dranko and V. A. Irikov, “The ‘cost-effectiveness’ method as a tool for selecting priority projects of an enterprise,” Upravl. Uchet, No. 4, 15–20 (2011).
B. G. Litvak, V. V. Topka, P. V. Gorskii, and P. S. Bulushev, “Automated expert evaluation system (AEES),” State Registration Certificate of Computer Program (1991).
B. G. Litvak, Expert Information. Methods of Obtaining and Analysis (Radio Svyaz’, Moscow, 1982) [in Russian].
Ch. Papadimitriou and K. Steiglitz, Combinatorial Optimization: Algorithms and Complexity (Dover, New York, 1998).
A. Kaufmann, Méthodes et modèles de la recherche opérationnelle (Dunod, Paris, 1968).
A. I. Orlov, Sustainability in Socio-Economic Models (Nauka, Moscow, 1979) [in Russian].
P. Yu. Chebotarev, “Method of row sums and models leading to it,” in Problems of Computerization and Statistical Data Processing, Collection of Articles (VNIISI, Moscow, 1989), No. 3, pp. 94–110 [in Russian].
P. Yu. Chebotarev and E. Shamis, “Characterizations of scoring methods for preference aggregation,” Ann. Operat. Res. 80, 299–332 (1998).
V. G. Gorskii, A. I. Orlov, and A. A. Gritsenko, “The method of agreement of clustered rankings,” Autom. Remote Control 61, 506 (2000).
E. C. Harrington, “Decisibility function,” Industr. Quality Control 21 (10) (1965).
R. J. Dawson and C. W. Dawson, “Practical proposals for managing uncertainty and risk in project planning,” Int. J. Project Manage. 16, 299–310 (1998).
V. V. Topka, “Lexicographic solution of two-objective project planning problem under constrained reliability index,” J. Comput. Syst. Sci. Int. 55, 877 (2014).
F. P. Vasil’ev, Optimization Methods, new ed. (MTsNMO, Moscow, 2011), Vol. 2 [in Russian].
F. P. Vasil’ev, Optimization Methods, new ed. (MTsNMO, Moscow, 2011), Vol. 1 [in Russian].
A. N. Tikhonov and V. Ya. Arsenin, Solutions of Ill-Posed Problems (Nauka, Moscow, 1979; Halsted, New York, 1977).
A. B. Bakushinskii and A. V. Goncharskii, Iterative Methods for Solving Ill-Posed Problems (Nauka, Moscow, 1989) [in Russian].
A. B. Bakushinskii and A. V. Goncharskii, Ill-Posed Problems. Numerical Methods and Applications (Mosk. Gos. Univ., Moscow, 1989) [in Russian].
A. V. Nazin and A. S. Poznyak, Adaptive Choice of Variants: Recurrent Algorithms (Nauka, Moscow, 1986) [in Russian].
M. Elkjaer, “Stochastic budget simulation,” Int. J. Project Manage. 18, 139–147 (2000).
Author information
Authors and Affiliations
Corresponding author
Additional information
Translated by O. Pismenov
Rights and permissions
About this article
Cite this article
Topka, V.V. Selection of Priority Areas in Research and Development. J. Comput. Syst. Sci. Int. 58, 616–625 (2019). https://doi.org/10.1134/S1064230719040142
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1064230719040142