Salbek M. Beketov

Current decision support systems for recommending labor resource allocation and generating production schedules in the systems with decentralized technological process control often fail to account for the impact of participants’ communication strategies on the shifts in target performance indicators, which depend on the alignment between local goals of production units and the global objectives of the system. The goal of the present study is to develop an approach for determining optimal communication parameters among intelligent agents to achieve system-level performance targets using the previously developed multiagent systems (MAS) for optimizing technological processes. The research investigates how agent constraint systems influence both overall system welfare and the individual welfare of agents, considering the shifts in their objective functions driven by preferred communication strategies. A workflow is developed to identify effective constraints. Using this workflow, the study provides recommendations for assigning regional field development plans, accounting for participants’ tendencies toward cooperation. On data where the potential for increasing the region’s flow rate through optimization of labor resource allocation and scheduling of well intervention operations (GTO) does not exceed 6%, the presented solution enabled the development of field plans that result in an additional 1% increase in the predicted oil production region’s flow rate on top of the gain achieved through resource allocation optimization.

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.

The research is dedicated to the advancement of methodological and instrumental foundations for team formation optimization in software projects, particularly in light of the increasing complexity and scale of such projects. The issue can be attributed to the intrinsic complexity of establishing and resolving the challenge of assembling the most effective project team. This research presents a model for the multi-criteria optimization of team composition in software pro­jects. The objective is to provide the management entity with a set of Pareto-optimal project team compositions for the implementation of a specific project. The study reviews existing methods of team formation and develops an algorithm and a mathematical multi-criteria model for optimizing the composition of a project team. The practical application of the model is illustrated by a case study that demonstrates the Pareto-optimal frontier of project team compositions in the time-labor plane. The research aims to enhance the predictability and manageability of software projects by employing a scenario-based approach during the team-building phase of the project. This study is relevant to stakeholders involved in software project management, including project managers, human resource professionals, and company management in general, seeking to implement methods to optimize team composition in project delivery.

Background. The research is devoted to the development of a model for the formation of optimal team composition for projects in general, and for innovative ones in particular, which are the basis of economic progress in the modern information society. The problem lies in the need to improve the efficiency and effectiveness of projects by optimizing the composition of teams. The aim of the study is to create a mathematical model for the formation of project teams, taking into account factors such as qualifications, productivity and innovative potential of participants. Materials and methods. The methodological and instrumental basis of the research was made up of general scientific and special optimization methods, the basics of cybernetics, and mathematical modeling. Results. The paper examines existing approaches to team building and develops an algorithm that minimizes personnel costs while maintaining high efficiency. The practical application of the model is demonstrated by the example of IT projects, which shows the possibilities of optimizing human resources and increasing productivity. The model ensures the optimal composition of the project team, which in turn contributes to the economic progress of project-oriented enterprises. Conclusions. The research is aimed at improving project management methods and models and may be useful for project managers, HR specialists and company management seeking to implement methods to optimize the composition of teams in the implementation of projects. The implementation of the developed model can help to increase the predictability and manageability of projects, which is especially important in the context of the growing complexity and scale of modern projects.

Данная работа посвящена разработке цифрового инструмента для автоматизации процессов сбора, хранения и обработки данных. В рамках исследования рассматриваются вопросы поддержания актуальности данных для цифровых инструментов исследования социально-экономических систем за счет адаптивных средств синхронизации данных с открытыми источниками. В исследовании поднимаются проблемы обработки больших данных, связанные с особенностями источников данных и соответствующих им проблем с качеством данных и непостоянством структур данных. На основании проанализированной информации разрабатываются функциональные требования к инструменту работы с данными с учетом особенностей источников данных, а также требований к использованию данных со стороны вычислительных моделей социально-экономических систем. Результатом работы является цифровой инструмент автоматизации процессов сбора, хранения и обработки данных, реализованный в качестве функционального модуля цифровой платформы инновационного развития регионов. Разработанное решение может быть адаптировано для аналогичных конфигурируемых систем хранения и обработки данных, в частности в цифровых платформах. Исследование реализовано в рамках проекта по разработке цифровой платформы региональной инновационной системы Российской Федерации как драйвера устойчивого развития. ФинансированиеИсследование выполнено при поддержке Министерства науки и высшего образования Российской Федерации (государственное задание № 075-03-2024-004 от 17.01.2024).

The main aspects of three concepts––human capital, innovation projects, and simulation modeling––are considered, and a simulation model is proposed to describe the role of human capital in innovation projects. This high-level abstraction model is intended to study the role of the social component in the organizational structure of an innovation project in a general context (at the level of an economic sector, an enterprise, or part of an enterprise). It is treated primarily as a tool for tracking the dynamics of projects considering the state of human capital of the system. The model consists of two main components, namely, a basic simulation model in system dynamics terms and an agent-based component of the model describing human capital dynamics. The model is a conceptual tool that requires calibration and refinement when being implemented in a particular organization.

Рассмотрены основные аспекты концепций человеческого капитала, инновационных проектов и имитационного моделирования, на основе чего предложена имитационная модель, описывающая роль человеческого капитала в инновационных проектах. Разработанная модель высокого уровня абстракции создана для исследования роли социального компонента в организационной структуре инновационного проекта в общем контексте (на уровне отрасли, предприятия, части предприятия) и рассматривается прежде всего как инструмент для отслеживания динамики проектов с учетом состояния человеческого капитала системы. Модель состоит из двух основных частей: базовой имитационной модели, выполненной на языке системной динамики, и агентного компонента модели, описывающего динамику человеческого капитала. Модель представляет собой концептуальный инструмент, требующий калибровки и доработки для применения к конкретной организации. The main aspects of three concepts––human capital, innovation projects, and simulation modeling––are considered, and a simulation model is proposed to describe the role of human capital in innovation projects. This high-level abstraction model is intended to study the role of the social component in the organizational structure of an innovation project in a general context (at the level of an economic sector, an enterprise, or part of an enterprise). It is treated primarily as a tool for tracking the dynamics of projects considering the state of human capital of the system. The model consists of two main components, namely, a basic simulation model in system dynamics terms and an agent-based component of the model describing human capital dynamics. The model is a conceptual tool that requires calibration and refinement when being implemented in a particular organization.