Objectives. The authors conduct an analytical review of available optimization methods and simulation tools to identify their key features, effectiveness, and possible applications. The aim was to form an integrated picture of modern approaches, which may facilitate decision making when selecting the most appropriate method for a particular task. The key objective was to review and classify various optimization tools, which of theoretical and practical value for developers of new models.Methods. Scientific publications and analytical materials were retrieved from specialized databases and technical documentation libraries.Results. The analysis and classification of existing optimization methods allowed the authors to identify their advantages, disadvantages, and application features, as well as to determine the relationship between theoretical concepts and their practical implementation. During the analysis, various optimization approaches were considered, covering both classical and modern simulation methods.Conclusions. The importance of informed selection of optimization methods, which raise the efficiency and accuracy of simulation procedures, is highlighted. The results obtained indicate the need for further study and comparative analysis of the methods used in practice in order to establish their efficiency and applicability in various scenarios. Future research directions include experimental testing of the effectiveness of various approaches based on several models in order to determine their advantages and disadvantages for a more informed selection of the method suitable for a particular task.

This study focuses on the development of a decision support system for complex production systems. As a promising approach to resource allocation challenges, the application of AI tools, particularly the multi-agent approach, is proposed. It is hypothesized that a decision support system based on multi-agent systems (MASs), grounded in an invariant ontology and utilizing game-theoretic tools, will enhance the effectiveness of managerial decisions by accounting for the inherent multi-agent nature of complex production systems, manifested in diverse objective functions and intricate interaction structures. The work identifies key features of intelligent agent interactions in multi-agent systems. Drawing on interaction types relevant to complex production systems and the selected MAS implementation architecture, an ontological model of multi-agent interactions and an ontological model for managing complex production systems are designed. The proposed models are tested using data from an oil and gas enterprise, and a formalization of utility functions for its agents is provided using game-theoretic tools. The resulting ontological model of multi-agent interactions in complex production systems is practical and easy to implement. It enables the design of MASs for diverse complex production systems, as demonstrated through a resource management case study in the oil and gas industry. Future study will refine the ontological model via industry-specific validation and expand the mathematical and computational tools for model implementation.

The paper aims at the design of a digital tool for analyzing the impact of scientific and technological progress on socioeconomic problems and sustainable development of the region. The research focuses on the consistent development of a digital platform for analyzing and visualizing digital data on regional innovation development, as well as predicting the sustainable development of regions based on the available regional infrastructure of innovation systems and the Russian regions' cluster structure. When designing the digital platform, we gave special attention to ensuring efficient data collection, processing, and analysis processes required for studying the socio-economic system. In the course of the work, an automated process of working with data was developed. The digital platform is being developed as a flexible tool for a wide range of users, from research centers, investors, and private enterprises to individual users interested in regional innovation development models. As part of the work, the process of selecting technical tools for the software implementation of the platform in terms of tasks and technical features of designing digital platforms is presented. The result of the work is a prototype of the Russian regional innovation system digital platform with the implemented functionality of a personal account, a module of simulation experiments, and various approaches to data analysis and visualization. The research is carried out as part of a project to develop a digital model of the regional innovation system of the Russian Federation as a driver of sustainable development.

Данная работа направлена на подготовку методологической базы для моделирования социально-экономических и социотехнических систем. Рассмотрены виды имитационного моделирования с точки зрения подбора оптимального решения в зависимости от особенностей объекта исследования и цели моделирования. Среди рассмотренных моделей, как инструмент для моделирования социально-экономических и социотехнических систем, наибольшее внимание уделяется гибридным моделям, позволяющим изучить анализируемый объект с разных сторон и на разных уровнях абстракции, комбинируя известные подходы имитационного моделирования. В дополнение, гибридные модели используются во многих сферах, таких как здравоохранение, экономика, экология, маркетинг, промышленные предприятия и производственные системы, что обеспечивает их универсальность, востребованность и эффективность данного подхода. В рамках исследования были проанализированы статьи базы научных публикаций Scopus, посвященные моделированию социально-экономических и социотехнических систем, имитационному моделированию и гибридным моделям. В данной статье рассмотрены базовые парадигмы имитационного моделирования и используемые методы для моделирования социально-экономических и социотехнических систем, произведена классификация по типу модели и гибридизации, освещены возможные комбинации типов гибридизации и применимость рассмотренных видов. Также выявлена тенденция к использованию гибридного моделирования в последние десятилетия, как средство для описания сложных социальных систем с различных точек зрения, где результаты подходов дополняют друг друга. В статье представлены предложения по интеграции инструментов технического моделирования в социально-экономические и социотехнические системы для обеспечения детерминированности системы. Результаты данного исследования могут быть использованы при выборе инструмента проектирования и прогнозирования поведения различных социально-экономических и социотехнических...

This article is devoted to the development of a high-level simulation model of tourism industry dynamics. The purpose of this study is to form recommendations for the recovery of the tourism industry from the effects of the pandemic. The resulting model considers domestic tourism from the point of view of the interdependence of the economic condition of the state, the contribution of the tourism industry to gross domestic product, the size of the tourist flow and the average income per tourist. In addition to describing the functional dependencies of the model elements, several experiments are proposed to test the logic of the elements’ relationships. System dynamics tools are used to develop the model. The study also examines the class of computable general equilibrium models as a tool for analyzing supply and demand in the market of tourist products.

This work is devoted to the development of a multiparametric optimization module for a digital management decision support tool based on simulation models. It is noted that the optimization of simulation models of complex socioeconomic and sociotechnical systems involves the generation of multiple scenarios of system development, their calculation, and further comparison, which imposes additional requirements on the optimization algorithms used. Moreover, complex socioeconomic and sociotechnical systems are characterized by a multiplicity of goals, which leads to multiparametric optimization. The result of the work is the algorithm for solving the problem of optimization of multiparametric scenario calculations using the example of a two-parameter optimization problem. The scope of the calculation optimization problem is to form the optimal set of scenarios that will ensure satisfactory computing time and, at the same time, give a representative scenario calculation result. Thus, the contribution of the current research is to formalize the processes of optimizing the parameters of simulation models of complex systems. In the course of the study, existing approaches to process optimization are considered. Based on the analysis of existing approaches to the formation of an optimal set of scenarios, ways to improve the algorithm type using approaches to scenario reduction or the introduction of genetic algorithms for the formation of an optimal set of scenarios are proposed. This work is carried out within a project to develop a digital tool to support managerial decision-making in sociotechnical and socioeconomic systems.