Foresight of Volga Federal District Innovation System Development using a Multi-Objective Genetic Algorithm

Abstract

The application of simulation modeling in public administration is under study at the level of interregional interaction in specific federal districts. The main indicator for development success of a particular federal district is the natural growth of its population. For this purpose, a model of foresight of federal district innovation system development based on the use of a multi-objective genetic algorithm was proposed. Stages of this foresight included preparation of statistical data for clusters, obtaining predictive functions for clusters and Pareto frontiers of predictive functions, and planning synergy effects of clusters of regions and the entire federal district. In this case, to increase the synergy effect of a federal district, investment resources and research and development (R&D) costs were planted to be redirected to those regions where economic and financial resources are insufficient. This will eventually increase the average per capita income of the population in the regions of the federal district, which will lead to population growth in these regions. If R&D costs are redistributed, there are also information and logistics interactions that confirm the practical effectiveness of the open innovation model within the federal district. For the Volga Federal District, this foresight resulted in its total positive reserve for R&D in the amount of 8,412 million rubles. It should be forwarded to the Samara Region. Then, the synergy effect of the whole Volga Federal District will be equal to 429,344 million rubles.  

Keywords

• foresight
• intercluster interaction
• multi-objective genetic algorithm
• simulation modeling