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This article presents study results of the region's sustainable development possibility, thus improving the population's life quality using cognitive simulation methods of complex systems. The main theoretical provisions of cognitive modeling developed and tested earlier in various socioeconomic system modeling are briefly outlined. The cognitive modeling application's mathematical apparatus and CMCS software No. 2018661506 system were developed using quantitative data from one of Russia's southern regions (Rostov oblast). The task was to study the region, model, understand, explain, and develop possible situation development scenarios, and foresee this complex system's possible future outcome. The main statistical socioeconomic indicators of the state region were studied and processed. Data analysis necessary for developing and researching a cognitive model is given. The regional economic mechanism cognitive model is a functional graph consisting of quantitative and qualitative concepts. Between them, relationships are given in the form of functions, which is the novelty of research. The results of several scenarios of impulse modeling are presented, making it possible to predict future desirable and undesirable processes in the system. Scenario analysis was carried out, making it possible to propose a number of recommendations for the region's sustainable development. A direction for the region's development of further cognitive research is proposed. [ABSTRACT FROM AUTHOR]

One of the key tools in an organization's performance management is the goal tree, which is used for solving both direct and inverse problems. This research deals with goal setting based on a model of the future by presenting the goal and subgoal in the form of concrete quantitative and qualitative characteristics and stepwise formation of factors. A stepwise solution to a factor generation problem is considered on the basis of mathematical symmetry. This paper displays an algorithm for solving hierarchical inverse problems with constraints, which is based on recursively traversing the vertices that constitute the separate characteristics. Iterative methods, modified for the case of nonlinear models and the calculation of constraints, were used to generate solutions to the subproblems. To realize the algorithm, the object-oriented architecture, which simplifies the creation and modification of software, was elaborated. Computational experiments with five types of models were conducted, and the solution to a problem related to fast-food restaurant profit generation was reviewed. The metrics of remoteness from set values and t-statistics were calculated for the purpose of testing the received results, and solutions to the subproblems, with the help of a mathematical package using optimization models and a method of inverse calculations, were also provided. The results of computational experiments speak to the compliance of the received results with set constraints and the solution of separate subproblems with the usage of the mathematical package. The cases with the highest solution accuracy reached are specified. [ABSTRACT FROM AUTHOR]