Subject. We address the planning of programs for innovative development of the region, which are based on simultaneous investment, production and financial planning. Objectives. The aim is to create a scientifically sound flexible management model that would consider the specificity of cyclical development of industrial region’s innovative system and the level of its socio-economic development, help overcome the economic determinism of territories, and boost the economic growth. Methods. The regional model of planning the innovative development programs implies global optimization of domestic current costs of research and development (R&D) of the industrial region, depending on its investment planning, and based on data on trends in fixed investments in the region; on production planning, according to data on trends in GRP; and on financial planning, based on data on trends in accounts payable of organizations. Results. We created a regional model for planning the innovative development programs. It rests on simultaneous investment, production and financial planning. The model has certain implementation features. The most elaborate for solving the problem under review is a pattern search algorithm. Adding this algorithm as a hybrid function for a genetic algorithm enables to achieve a sufficiently high-quality solution to the optimization problem. In contrast, adding the interior point method as a hybrid function does not always significantly improve the quality of global optimization. Conclusions. The presented model helps government entities make better decisions regarding the planning of innovative development of the country’s industrial regions.
Brigham E.F., Gapenski L.C., Daves P.R. Intermediate Financial Management. Orlando, The Dryden Press, 4th ed., 1993, 1122 p.
Kruschwitz L., Lorenz D. Investitionsrechnung. De Gruyter Oldenbourg Verlag, 2019, 427 p.
Limitovskii M.A., Limitovskaya E.V. Investitsionnye proekty i real'nye optsiony na razvivayushchikhsya rynkakh [Investment projects and real options in developing markets]. Moscow, Yurait Publ., 2014, 486 p.
Naumenkova S.V., Glazun O.I. [The methods of the quantitative analysis and forecasting of managerial processes by financial activity of the enterprise]. Вiсник Украiнськоi академii банкiвськоi справи, 2002, no. 1, pp. 32–36. URL: Link (In Russ.)
Hahn G.J., Kuhn H. Simultaneous Investment, Operations, and Financial Planning in Supply Chains: A Value-Based Optimization Approach. International Journal of Production Economics, 2012, vol. 140, iss. 2, pp. 559–569. URL: Link
Nedosekin A.O., Abdulaeva Z.I. Modeli i metody finansovogo planirovaniya: monografiya [Models and methods of financial planning: a monograph]. St. Petersburg, Polytechnic University Publ., 2013, 176 p.
Rytikov S.A., Bogdanov A.V., Kulakov A.D. [Applying the models of simultaneous investment and financial planning for preliminary appraisal of investment projects in a special economic zone]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2014, no. 40, pp. 57–68. URL: Link (In Russ.)
Dinges E.V., Pozdeeva S.N. Metody planirovaniya investitsionno-finansovoi deyatel'nosti predpriyatii dorozhnogo khozyaistva: monografiya [Methods of planning investment and financial activities of road industry enterprises: a monograph]. Moscow, MADI Publ., 2018, 116 p.
Gershman M.A. [Innovation development programmes for the State-owned companies: First results]. Forsait = Foresight-Russia, 2013, vol. 7, no. 1, pp. 28–43. URL: Link (In Russ.)
Stroeva O.A. [Workout of the programme of innovation development of regional economic systems]. Vestnik UrFU. Seriya ekonomika i upravlenie = Bulletin of Ural Federal University. Series Economics and Management, 2011, no. 5, pp. 115–124. (In Russ.) URL: Link
Da Silva F.M., de Araujo Querido Oliveira E.A., de Moraes M.B. Innovation Development Process in Small and Medium Technology-based Companies. RAI Revista de Administração e Inovação, 2016, vol. 13, iss. 3, pp. 176–189. URL: Link
Vasconcellos E.P.G., Muritiba S.N., Prado S.M.A. et al. Analyzing R&D Projects on Health Products. RAI Revista de Administração e Inovação, 2016, vol. 13, iss. 3, pp. 199–210. URL: Link
Feoktistova O.A. [Planning of the research costs: The project-based approach]. Finansovyi zhurnal = Financial Journal, 2014, no. 1, pp. 69–80. URL: Link (In Russ.)
Gaponenko V.F. [The questions of costs’ planning on implementation of the scientific research works in the system of the Interior Ministry of Russia]. Trudy Akademii upravleniya MVD Rossii = Proceedings of Management Academy of the Ministry of the Interior of Russia, 2018, no. 1, pp. 58–62. URL: Link (In Russ.)
Yashin S., Yashina N., Koshelev E. et al. Foresight of Volga Federal District Innovation System Development using a Multi-Objective Genetic Algorithm. International Journal of Technology, 2020, vol. 11, no. 6, pp. 1171–1180. URL: Link
Polyanin A., Pronyaeva L., Pavlova A., Fedotenkova O., Rodionov D. Integrated Approach for Assessing the Economic Security of a Cluster. International Journal of Technology, 2020, vol. 11, iss. 6, pp. 1148–1160. URL: Link
Tashenova L., Babkin A., Mamrayeva D., Babkin I. Method for Evaluating the Digital Potential of a Backbone Innovative Active Industrial Cluster. International Journal of Technology, 2020, vol. 11, no. 8, pp. 1499–1508. URL: Link
Kalyanmoy D. Multi-objective Optimization Using Evolutionary Algorithms: An Introduction. New York, John Wiley & Sons, Inc., 2001.
Lopatin A.S. [Annealing method]. Stokhasticheskaya optimizatsiya v informatike = Stochastic Optimization in Computer Science, 2005, vol. 1, pp. 133–149. URL: Link (In Russ.)
Ingber L., Rosen B. Genetic Algorithms and Very Fast Simulated Reannealing: A Comparison. Mathematical and Computer Modelling, 1992, vol. 16, iss. 11, pp. 87–100. URL: Link90108-W
Conn A.R., Gould N.I.M., Toint Ph.L. A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds. SIAM Journal on Numerical Analysis, 1991, vol. 28, no. 2, pp. 545–572. URL: Link
Conn A.R., Gould N.I.M., Toint Ph.L. A Globally Convergent Augmented Lagrangian Barrier Algorithm for Optimization with General Inequality Constraints and Simple Bounds. Mathematics of Computation, 1997, vol. 66, no. 217, pp. 261–288.
Kolda T.G., Lewis R.M., Torczon V. A Generating Set Direct Search Augmented Lagrangian Algorithm for Optimization with a Combination of General and Linear Constraints. Sandia National Laboratories, August 2006, 44 p.
Babynin M.S., Zhadan V.G. [A primal interior point method for the linear semidefinite programming problem]. Zhurnal vychislitel'noi matematiki i matematicheskoi fiziki = Computational Mathematics and Mathematical Physics, 2008, vol. 48, no. 10, pp. 1780–1801. (In Russ.)
