2782-6333 4 18 2025 1-86

RAR RUS 7-23 Research Institute of Applied Materials Science, Almaz-Antey Concern, St. Petersburg, Russia Nefedova Lyubov MATHEMATICAL MODELS FOR ADAPTIVE DESIGN IN ADDITIVE MANUFACTURING The article examines the concept of the digital thread in additive manufacturing as a foundation for improving the economic efficiency of the production cycle through intelligent support at the design stage. A mathematical model and algorithmic procedure for the "Search and Selection of Knowledge Fragments" stage are proposed within the framework of the authors' development of the MAPE-K adaptive control model by incorporating the stages of search, reuse, and evaluation. It is shown that the most significant potential for increasing the productivity of additive manufacturing is concentrated at the design stage of digital product models and technological processes, where the application of ontological modeling and machine learning methods can significantly reduce labor intensity and improve the quality of decisions made. The study formalizes the task of searching and selecting knowledge fragments based on a combination of semantic and embedding representations. A multi-stage candidate selection procedure is proposed, including attribute filtering, embedding search, re-ranking, constraint validation, and selection based on diversity criteria. This approach allows combining the interpretability of ontologies with the scalability and robustness of ANN mechanisms. The results of the work include a model of the digital thread for additive manufacturing, a detailed description, and a system of mathematical support for the stage of searching and selecting fragments. The obtained results form the basis for building a digital thread for additive manufacturing, oriented towards a self-learning knowledge base and continuous model improvement. 10.48554/SDEE.2025.4.1 004.81 digital thread additive manufacturing decision support machine learning economic efficiency https://sustainable.spbstu.ru/article/2025.18.1/ sdee_2025_4_1.pdf

RAR RUS 24-37 0000-0002-5680-1937 Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian Federation Burlutskaya Zhanna Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia Sharko Polina sgutman@spbstu.ru Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Lundaeva Karina 0009-0009-6448-9486 Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Beketov Salbek METHOD OF MODELING MULTI-AGENT INTERACTIONS IN COMPLEX TECHNOLOGICAL PROCESSES This work is devoted to the study of the organizational system of technological processes, including the identification of typical agents, their target functions and strategies for interacting with each other during the functioning of the system. Within the framework of this study, it is proposed to consider the system of technological processes as a complex organizational system of an interdisciplinary nature with its corresponding features, including a multiplicity of target functions, internal uncertainty, distributed management and limited rationality of social elements. The aim of the work is to develop a method for modeling multi-agent interactions in complex technological processes. In the course of the work, the description of typical agents of the technological process system, their tasks and target functions are given. The result of the work is an ontological model of the organizational system of technological processes, as well as a method for modeling multi-agent interactions in complex technological processes based on it. As part of the approbation of the proposed method, a model of the technological process system in the oil and gas industry is developed. At the next stages of the study, it is planned to develop and programmatically implement algorithms for optimizing technological processes based on a multi-agent approach based on hybrid modeling of technological process systems as a set of processes modeled using simulation modeling and an organizational system of intelligent agents managing processes using a multi-agent approach. 10.48554/SDEE.2025.4.2 519.876.2 complex systems multi-agent interactions technological processes simulation modeling intelligent agents https://sustainable.spbstu.ru/article/2025.18.2/ sdee_2025_4_2.pdf

RAR RUS 38-48 Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia Karvanen Oleg W-8013-2019 57203897426 0000-0002-9703-5079 Peter the Great St. Petersburg Polytechnic University, Russian Federation Gintciak Aleksei gintsyak_am@spbstu.ru DECISION-MAKING ALGORITHM FOR OPTIMIZING CARGO STORAGE IN 3PL LOGISTICS COMPANIES The paper examines the efficiency indicators of cargo storage in 3PL logistics companies. A system of indicators of the efficiency of cargo placement in a warehouse is presented, divided into groups: an indicator of the efficiency of filling warehouse cells, an indicator of warehouse occupancy and an indicator of the relevance of the warehouse configuration. The indicator of the relevance of the warehouse configuration is of particular value for 3PL logistics companies, as it allows them to assess the compliance of current cell sizes taking into account the changing cargo composition and make strategic decisions about the need to change the warehouse configuration. A logical scheme of making decisions on measures to optimize the placement of goods in a warehouse, depending on the magnitude of the indicators, is presented. The results of the work can be used to build a comprehensive management system for the efficiency of cargo storage in 3PL logistics companies. 10.48554/SDEE.2025.4.3 658.511.3 3PL warehouse configuration location efficiency https://sustainable.spbstu.ru/article/2025.18.3/ sdee_2025_4_3.pdf

RAR RUS 49-63 Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian Federation Kozikova Diana SIMULATION MODELING OF THE PROCESSES OF INTEGRATING INNOVATIONS INTO THE EDUCATIONAL ACTIVITIES OF EDUCATIONAL ORGANIZATIONS This article presents a theoretical and methodological approach to investigating the processes of innovation integration into the educational activities of educational organizations, leveraging simulation modeling tools. Within the framework of a systems approach, an educational organization is conceptualized as a complex dynamic system. This allows for a more detailed analysis of the nonlinear processes involved in innovation implementation and their systemic consequences. Amidst rapid changes in the educational environment and the continuous emergence of new technologies, the importance of effective innovation integration becomes particularly crucial. The central outcome of this work is the development of a theoretical model that elucidates the systemic interconnections among elements of the educational environment under conditions of innovative change. This model facilitates the investigation of how various factors influence the success of innovation implementation and how they mutually interact. The study conducted a comparative analysis of the capabilities of discrete-event simulation, agent-based modeling, and system dynamics. This analysis aimed to assess their applicability for addressing innovation management tasks at various levels, ranging from operational to strategic. Methodological limitations and the complementary potential of each approach were identified. The practical significance of this research lies in establishing a framework for selecting appropriate modeling tools to design and evaluate the implications of innovation implementation within educational organizations. 10.48554/SDEE.2025.4.4 37.013.5 simulation modeling innovation integration educational organization systematic approach https://sustainable.spbstu.ru/article/2025.18.4/ sdee_2025_4_4.pdf

RAR RUS 64-86 Saint Petersburg Electrotechnical University "LETI", St. Petersburg, Russian Federation Danilenko Kirill 57144577800 St Petersburg Electrotechnical University “LETI”, St. Petersburg, Russia Brusakova Irina SUSTAINABILITY ANALYSIS OF AN ADAPTIVE DIGITAL ENTERPRISE BUSINESS MODEL IN A MULTI-COMPONENT SYSTEMS This paper develops a mathematical model of an adaptive business model for a digital enterprise operating in a multi-component environment and proves the conditions for its sustainability. The relevance of the research is determined by the fact that modern organizations are simultaneously exposed to physical, institutional, market, and technological factors; however, existing approaches consider these factors in isolation and do not provide formal justification for viability conditions. The methodological framework of the study integrates active systems theory, system dynamics, and nonlinear control theory. A causal loop diagram and a stock-flow diagram were constructed using the VENSIM simulation environment. The Input-to-State Stability (ISS) concept and the Lyapunov function method were applied for formal stability analysis. As a result, a model with two feedback loops was developed – a stability loop and an adaptation loop, with switching between them occurring through a critical stress threshold. The system was proven to possess ISS stability under three simultaneous conditions: boundedness of the external perturbation flow function, positive sensitivity of adaptation capacity to buffer magnitude, and positivity of the buffer replenishment function during stability periods. Numerical simulation of three scenarios confirmed the theoretical predictions and demonstrated the existence of an equilibrium attraction domain. The results expand the possibilities for quantitative analysis of organizational sustainability and can be applied for early threat detection, investment decision support, and digital platform strategy development. 10.48554/SDEE.2025.4.5 658.511.3 sustainability adaptive business model multi-component environment system dynamics paradoxical management Input-to-State Stability Lyapunov function resource buffers critical threshold https://sustainable.spbstu.ru/article/2025.18.5/ sdee_2025_4_5.pdf