Modeling of Motivation of Top Managers in Regional Management Structures Using a Multi-Objective Genetic Algorithm

Abstract

The purpose of this research is to create a model for evaluating financial and non-financial motivation of top managers in regional and district management structures. For this purpose, the efficiency of inter-cluster interaction within one federal district is evaluated using a system of factors of socio-economic development of Russian regions, which directly affect the natural population growth in the district's regions. Since people's priorities are more important, the effectiveness of their implementation should be financially motivated. It is proposed to motivate the implementation of objectives affecting the State as a whole in an intangible way. To solve this problem, the multi-objective genetic algorithm method is used, which makes it possible to obtain the Pareto frontier for the dual-objective function of natural population growth, all the solutions of which are equally optimal. Choosing any point of the Pareto frontier, you can find in it fractions of financial and non-financial motivation of top managers. They are determined by the proximity to the extreme points of the Pareto frontier, where only one of the two regressions (motivations) is maximum.