Последние десятилетия для изучения проблем социальных и гуманитарных наук все чаще применяются вычислительные модели. Конференция направлена на создание площадки для открытого диалога между исследователями и практиками, заинтересованными в синтезе информатики и социально-гуманитарных наук, для привлечения внимания, признания и лучшего понимания проблем симуляции и моделирования социально-экономических процессов.
Добро пожаловать на конференцию
“МОДЕЛИРОВАНИЕ И СИМУЛЯЦИЯ СОЦИАЛЬНО-ПОВЕДЕНЧЕСКИХ ФЕНОМЕНОВ В КРЕАТИВНЫХ СООБЩЕСТВАХ”
Тематика конференции
Благодаря междисциплинарной направленности конферен-ция объединяет исследователей в области социально-гуманитарных наук (например, экономики, социологии, теории организации, теории коммуникативного действия, менеджмента, социальной сложности, маркетинга и др.), исследования операций, вычислительного интеллекта, эконо-физики, агент-ориентированного моделирования, прикладной математики и т.д.
ИСТОРИЯ КОНФЕРЕНЦИИ
Моделирование и симуляция социально-поведенческих феноменов в креативных сообществах (MSBC-2019)
Моделирование и симуляция социально-поведенческих феноменов в креативных сообществах (MSBC-2022)
II Международная европейская конференция
Вильнюс, Литва
Материалы конференции:
Springer Proceedings MSBC-2022
(CCIS, volume 1717)
Mathematics Special Issue
(ISSN 2227-7390)Моделирование и симуляция социально-поведенческих феноменов в креативных сообществах (MSBC-2024)
III Международная конференция
Алматы, Казахстан
Материалы конференции:
Springer Proceedings MSBC-2024
(CCIS, volume 2211)Моделирование и симуляция социально-поведенческих феноменов в креативных сообществах (MSBC-2026)
IV Международная конференция
Ташкент, Узбекистан
Материалы конференции:
Моделирование и симуляция социально-поведенческих феноменов в креативных сообществах (MSBC-2028)
V Международная конференция
Информация появится позднее
ОРГАНИЗАТОРЫ КОНФЕРЕНЦИИ
СООРГАНИЗАТОРЫ КОНФЕРЕНЦИИ
МЕЖДУНАРОДНЫЙ ПРОГРАММНЫЙ КОМИТЕТ
Леонидас Сакалаускас
(Leonidas Sakalauskas), Ph.D.,
Университет Витовта Великого,
Литва
Председатель
Члены Международного программного комитета
– Prof. Dr. Nilufar Abdurakhmonova, National University of Uzbekistan, Uzbekistan
– Prof. Marat Akhmet, Middle East Technical University, Turkey
– Prof. Nitin Agarwal, University of Arkansas at Little Rock, USA
– Prof. Mirsaid Aripov, National University of Uzbekistan, Uzbekistan
– Prof. Marat Akhmet, Middle East Technical University, Turkey
– Prof. Nitin Agarwal, University of Arkansas at Little Rock, USA
– Prof. Mirsaid Aripov, National University of Uzbekistan, Uzbekistan
– Prof. Fuad Aleskerov, Higher School of Economics, Russia
– Prof. Rakhman Alshanov, Turan University, Kazakhstan
– Prof. Dr. Elena Andreeva, Hanover Medical School, Germany
– Prof. Dr. Juozas Augutis, Vytautas Magnus University, Lithuania
– Prof. Adil Bagirov, Federation University Australia, Australia
– Prof. Tomas Balezentis, LCSS Institute of Economics and Rural Development, Lithuania
– Prof. Tomas Balezentis, LCSS Institute of Economics and Rural Development, Lithuania
– Prof. Laura Baitenova, Turan University, Kazakhstan
– Prof. Dr. Alexis Belianin, Higher School of Economics, Russia
– Prof. Dr. Cathal MacSwiney Brugha, University College Dublin, Ireland
– Prof. Gulmira Bekmanova, L.N. Gumilyov Eurasian National University, Kazakhstan
– Prof. Dr. Gordon Dash, University of Rhode Island, USA
– Prof. Dorien DeTombe, EWG on Ethics and OR, Netherlands
– Prof. Vitalijus Denisovas, Klaipeda University, Lithuania
– Prof. Dr. Aiste Dirzyte, Mykolas Romeris University, Lithuania
– Prof. Yoqub Ergashov, National University of Uzbekistan, Uzbekistan
– Prof. Yoqub Ergashov, National University of Uzbekistan, Uzbekistan
– Prof. Dr. Walter Leal Filho, Hamburg University of Applied Sciences, Germany
– Prof. Ayrat Gatiatullin, Kazan Federal University, Russia
– Prof. Ayrat Gatiatullin, Kazan Federal University, Russia
– Prof. Ignacio Grossman, Carnegie Mellon University, USA
– Prof. Aybibi Iskandarova, National University of Uzbekistan, Uzbekistan
– Prof. Jasur Israilov, Namangan State University, Uzbekistan
– Prof. Aybibi Iskandarova, National University of Uzbekistan, Uzbekistan
– Prof. Jasur Israilov, Namangan State University, Uzbekistan
– Prof. Dr. Nella Israilova, Kyrgyz State Technical University, Kyrgyzstan
– Prof. Nina Kaiji, University of Rhode Island, USA
– Prof. Dr. George Kleiner, Financial University, Russia
– Prof. Dr. Mikhail Kovalyov, United Institute of Informatics Problems, Belarus
– Prof. Dr. Tomas Krilavicius, Vytautas Magnus University, Lithuania
– Prof. Dr. Tomas Krilavicius, Vytautas Magnus University, Lithuania
– Prof. Suria Kumacheva, St. Petersburg State University, Russia
– Prof. Dr. Mindaugas Kurmis, Klaipeda University, Lithuania
– Prof. Dr. Mindaugas Kurmis, Klaipeda University, Lithuania
– Prof. Nelson Maculan, University Federal of Rio de Janeiro, Brasil
– Prof. Oleksandr Makarenko, Kyiv Technical University, Ukraine
– Prof. Dr. Madina Mansurova, Al-Farabi Kazakh National University, Kazakhstan
– Prof. Dr. Vladimir Mazalov, Petrozavodsk University, Russia
– Prof. Davlatyor Mengliyev, Urgench Branch of Tashkent University, Uzbekistan
– Prof. Gediminas Merkys, Vytautas Magnus University, Lithuania
– Prof. Davlatyor Mengliyev, Urgench Branch of Tashkent University, Uzbekistan
– Prof. Gediminas Merkys, Vytautas Magnus University, Lithuania
– Prof. Peep Miidla, Estonian Center of Industrial Mathematics, Estonia
– Prof. Marek Miłosz, Lublin University of Technology, Poland
– Prof. Shynar Mussiraliyeva, Al-Farabi Kazakh National University, Kazakhstan
– Prof. Dr. Elmira Nazirova, Tashkent University of Information technologies, Uzbekistan
– Prof. Batyrkhan Omarov, Al-Farabi Kazakh National University, Kazakhstan
– Prof. Dina Oralbekova, Satbayev University, Kazakhstan
– Prof. Aziz Otemisov, Karakalpak State University, Uzbekistan
– Prof. Dr. Diana Rakhimova, Al-Farabi Kazakh Natioal University, Kazakhstan
– Prof. Dina Razakova, Turan University, Kazakhstan
– Prof. Dr. Sankar Kumar Roy, Vidyasagar University, West Bengal, India
– Dr. Maxim Rybachuk, Financial University, Russia
– Prof. Maxatbek Satymbekov, Al-Farabi Kazakh National University, Kazakhstan
– Prof. Aleksandr Savostyanov, Novosibirsk State University, Russia
– Prof. Aleksandr Savostyanov, Novosibirsk State University, Russia
– Prof. Roman Slowinski, Poznan University, Poland
– Prof. Christos Skiadas, Technical University of Crete, Greece
– Prof. Alexis Tsoukias, LAMSADE, France
– Prof. Dr. Ualsher Tukeyev, Al-Farabi Kazakh National University, Kazakhstan
– Prof. Ulugbek Tuliyev, National University of Uzbekistan, Uzbekistan
– Prof. Mafura Uandykova, NarXoz University, Kazakhstan
– Prof. Sigitas Vaitkevicius, Vytautas Magnus University, Lithuania
– Prof. Gerhard-Wilhelm Weber, Poznan University, Poland
– Prof. Adilson Xavier, University Federal Rio de Janeiro, Brasil
– Prof. Edmundas-Kazinieras Zavadskas, Vilnius Technical University, Lithuania
ОРГАНИЗАЦИОННЫЙ КОМИТЕТ
Раима Ширинова
(Raima Shirinova), Ph.D.,
Национальный университет Узбекистана, Узбекистан
Сопредседатель
Нилуфар Абдурахмонова
(Nilufar Abdurakhmonova), Ph.D.,
Национальный университет Узбекистана, Узбекистан
Сопредседатель
Члены Организационного комитета
– Леонидас Сакалаускас (Leonidas Sakalauskas), Университет Витовта Великого, Литва
– Максим Рыбачук (Maxim Rybachuk), Финансовый университет при Правительстве РФ, Россия
– Эльмира Назирова (Elmira Nazirova), Ташкентский университет информационных технологий, Узбекистан
– Неринга Урбонайте (Neringa Urbonaite), Вильнюсский университет, Литва
ПЛЕНАРНЫЕ ДОКЛАДЧИКИ
Prof. Dr. Mersaid Aripov,
Uzbek National University
of Mirzo Ulugbek, Uzbekistan
Prof Dr. Vladimir Mazalov,
St. Peterburg State
University, Russia
Prof. Dr. Lina Volodzkienė,
Mykolas Romeris
University, Lithuania
Prof. Dr. Vladimer Papawa,
Tbilisi State
University, Georgia
Prof. Dr. Ualsher Tukeyev,
Al-Farabi Kazakh National
University, Kazakhstan
Prof. Dr. Sankar Kumar Roy,
Vidyasagar University,
India
Dr. Maimaiti Mieradilijiang,
Xinjiang University,
China
ПРЕДВАРИТЕЛЬНАЯ ПРОГРАММА КОНФЕРЕНЦИИ
* Время в программе указано по часовому поясу GMT+5 (Ташкент, Узбекистан)
Registration
Conference Opening & Welcome Remarks
Chairman
- Leonidas Sakalauskas (Vytautas Magnus University, Lithuania)
Plenary Session
Chairman
- Leonidas Sakalauskas (Vytautas Magnus University, Lithuania)
Ualsher Tukeyev
(Almaty, Kazakhstan)
Prof. Dr. Ualsher Tukeyev,
Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Kazakhstan
COMPUTATIONAL THINKING AS CREATIVE MODELING IN AI-ASSISTED INTELLIGENT PROGRAMMING
AI-assisted programming tools and large language models have fundamentally changed software development. Today, AI can generate full codebases, suggest architectures, create tests, and even assemble deployable systems from high-level prompts. While this dramatically accelerates implementation, it does not eliminate the need for structured problem formulation and model-level reasoning. This plenary lecture proposes a modeling-centered interpretation of computational thinking in the era of AI-assisted development. Rather than equating computational thinking with coding, we argue that its constructive phase lies in creative modeling—the explicit design of executable computational models grounded in domain constraints, representation choices, and validation criteria. In practice, creative modeling involves: (1) defining the problem space and non-negotiable constraints, (2) selecting or designing appropriate computational representations that explicitly encode domain structure and constraints, (3) constructing hybrid executable models, and (4) specifying validation procedures independent of implementation details. AI-assisted programming then operates as an implementation accelerator within this structured workflow. The approach is illustrated through a hybrid symbolic–neural model of Kazakh morphological structure, where constraint-aware modeling ensures structural correctness while neural components enableplenary generalization. Experimental results demonstrate that explicitly modeled constraints improve robustness and reduce structurally invalid outputs compared to unconstrained neural solutions. The lecture concludes by outlining when creative modeling becomes essential: in constraint-sensitive systems, hybrid architectures, explainable AI applications, and validation-critical domains. In such contexts, intelligent programming requires not only code generation but explicit model construction and verification. This perspective reframes the role of the human engineer: from code producer to model architect responsible for structural integrity and correctness in AI-driven systems.
Mersaid Aripov
(Tashkent, Uzbekistan)
Prof. Dr. Ualsher Tukeyev,
National University of Uzbekistan named after Mirzo Ulugbek, Uzbekistan
LLM FOR ASPECT-BASED SENTIMENT ANALYSIS OF UZBEK SERVICE SECTOR REVIEWS
The rapid growth of digital platforms has transformed online consumer reviews into an important source of social-behavioural data, reflecting how citizens evaluate services, express satisfaction or dissatisfaction, and communicate expectations toward businesses and institutions. In emerging digital societies, such data can support evidence-based service improvement and provide valuable insight into patterns of public perception. However, for low-resource languages such as Uzbek, the practical use of online review data remains limited by the lack of large, high-quality annotated datasets and robust language technologies. This talk addresses that gap by presenting a large language model (LLM)-driven framework for Aspect-Based Sentiment Analysis (ABSA) of Uzbek online service reviews, with a focus on the banking, retail, and HoReCa sectors. The proposed direction is closely aligned with the conference’s interest in applying computational and AI-based methods to social-behavioural phenomena. Unlike conventional sentiment analysis, which reduces reviews to broad positive or negative labels, ABSA enables a more fine-grained understanding of how users judge specific aspects of service experience, such as staff behaviour, response speed, pricing, delivery quality, product reliability, and digital interaction quality. This makes ABSA especially relevant for modelling consumer perceptions as complex social signals rather than simple emotional reactions. In multilingual and low-resource contexts, such modelling is not only a technical challenge but also a social one, because it determines whether digitally expressed public opinion can be transformed into structured knowledge for decision-making and service redesign. The Uzbek case is particularly important because it represents a growing digital market where user-generated content is increasing, while computational resources for language understanding remain underdeveloped. The proposed research framework is based on the collection and processing of more than 30,000 Uzbek-language consumer reviews from the Sharh platform. To overcome the bottleneck of manual annotation, the study employs open-source LLMs, including models such as Llama 3 and Mistral, as annotation assistants for aspect extraction and sentiment labelling.
Mieradilijiang Maimaiti
(Ürümqi, China)
Associate Professor, Dr. Mieradilijiang Maimaiti,
School of Computer Science, Xinjiang University, China
LARGE LANGUAGE MODELS FOR UNDER-RESOURCED LANGUAGES: FROM TEXT UNDERSTANDING TO MULTIMODAL RETRIEVAL
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing and multimodal tasks. However, their performance remains limited in under-resourced language scenarios due to insufficient training data, weak linguistic coverage, and a lack of multimodal supervision. This talk presents our recent efforts to advance LLMs for under-resourced languages in both text-only and multimodal settings. The presentation begins with a brief overview of the foundations of LLMs, examining their applications, challenges, and limitations in under-resourced NLP tasks. Subsequently, we explore recent research on LLM-based machine translation, covering instruction data construction, prior knowledge integration, chain-of-thought prompting, and linguistically aware translation strategies for under-resourced and morphologically rich languages. The focus then shifts to our recent progress in multimodal learning, highlighting the automatic construction of multimodal corpora, efficient multimodal fusion, and vision-aware retrieval mechanisms for under-resourced translation and caption generation. Finally, the discussion turns to our ongoing explorations of retrieval-augmented generation (RAG) and the development of custom large language models for multilingual understanding and generation in under-resourced languages.
Coffee Break
Contributed Sessions 1
Lunch
Contributed Sessions 2
Coffee Break
Contributed Sessions 3
Welcome Party
Registration
Conference Opening & Welcome Remarks
Chairman
- Leonidas Sakalauskas (Vytautas Magnus University, Lithuania)
Plenary Session
Chairman
- Leonidas Sakalauskas (Vytautas Magnus University, Lithuania)
Ualsher Tukeyev
(Almaty, Kazakhstan)
Prof. Dr. Ualsher Tukeyev,
Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Kazakhstan
COMPUTATIONAL THINKING AS CREATIVE MODELING IN AI-ASSISTED INTELLIGENT PROGRAMMING
AI-assisted programming tools and large language models have fundamentally changed software development. Today, AI can generate full codebases, suggest architectures, create tests, and even assemble deployable systems from high-level prompts. While this dramatically accelerates implementation, it does not eliminate the need for structured problem formulation and model-level reasoning. This plenary lecture proposes a modeling-centered interpretation of computational thinking in the era of AI-assisted development. Rather than equating computational thinking with coding, we argue that its constructive phase lies in creative modeling—the explicit design of executable computational models grounded in domain constraints, representation choices, and validation criteria. In practice, creative modeling involves: (1) defining the problem space and non-negotiable constraints, (2) selecting or designing appropriate computational representations that explicitly encode domain structure and constraints, (3) constructing hybrid executable models, and (4) specifying validation procedures independent of implementation details. AI-assisted programming then operates as an implementation accelerator within this structured workflow. The approach is illustrated through a hybrid symbolic–neural model of Kazakh morphological structure, where constraint-aware modeling ensures structural correctness while neural components enableplenary generalization. Experimental results demonstrate that explicitly modeled constraints improve robustness and reduce structurally invalid outputs compared to unconstrained neural solutions. The lecture concludes by outlining when creative modeling becomes essential: in constraint-sensitive systems, hybrid architectures, explainable AI applications, and validation-critical domains. In such contexts, intelligent programming requires not only code generation but explicit model construction and verification. This perspective reframes the role of the human engineer: from code producer to model architect responsible for structural integrity and correctness in AI-driven systems.
Mersaid Aripov
(Tashkent, Uzbekistan)
Prof. Dr. Ualsher Tukeyev,
National University of Uzbekistan named after Mirzo Ulugbek, Uzbekistan
LLM FOR ASPECT-BASED SENTIMENT ANALYSIS OF UZBEK SERVICE SECTOR REVIEWS
The rapid growth of digital platforms has transformed online consumer reviews into an important source of social-behavioural data, reflecting how citizens evaluate services, express satisfaction or dissatisfaction, and communicate expectations toward businesses and institutions. In emerging digital societies, such data can support evidence-based service improvement and provide valuable insight into patterns of public perception. However, for low-resource languages such as Uzbek, the practical use of online review data remains limited by the lack of large, high-quality annotated datasets and robust language technologies. This talk addresses that gap by presenting a large language model (LLM)-driven framework for Aspect-Based Sentiment Analysis (ABSA) of Uzbek online service reviews, with a focus on the banking, retail, and HoReCa sectors. The proposed direction is closely aligned with the conference’s interest in applying computational and AI-based methods to social-behavioural phenomena. Unlike conventional sentiment analysis, which reduces reviews to broad positive or negative labels, ABSA enables a more fine-grained understanding of how users judge specific aspects of service experience, such as staff behaviour, response speed, pricing, delivery quality, product reliability, and digital interaction quality. This makes ABSA especially relevant for modelling consumer perceptions as complex social signals rather than simple emotional reactions. In multilingual and low-resource contexts, such modelling is not only a technical challenge but also a social one, because it determines whether digitally expressed public opinion can be transformed into structured knowledge for decision-making and service redesign. The Uzbek case is particularly important because it represents a growing digital market where user-generated content is increasing, while computational resources for language understanding remain underdeveloped. The proposed research framework is based on the collection and processing of more than 30,000 Uzbek-language consumer reviews from the Sharh platform. To overcome the bottleneck of manual annotation, the study employs open-source LLMs, including models such as Llama 3 and Mistral, as annotation assistants for aspect extraction and sentiment labelling.
Mieradilijiang Maimaiti
(Ürümqi, China)
Associate Professor, Dr. Mieradilijiang Maimaiti,
School of Computer Science, Xinjiang University, China
LARGE LANGUAGE MODELS FOR UNDER-RESOURCED LANGUAGES: FROM TEXT UNDERSTANDING TO MULTIMODAL RETRIEVAL
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing and multimodal tasks. However, their performance remains limited in under-resourced language scenarios due to insufficient training data, weak linguistic coverage, and a lack of multimodal supervision. This talk presents our recent efforts to advance LLMs for under-resourced languages in both text-only and multimodal settings. The presentation begins with a brief overview of the foundations of LLMs, examining their applications, challenges, and limitations in under-resourced NLP tasks. Subsequently, we explore recent research on LLM-based machine translation, covering instruction data construction, prior knowledge integration, chain-of-thought prompting, and linguistically aware translation strategies for under-resourced and morphologically rich languages. The focus then shifts to our recent progress in multimodal learning, highlighting the automatic construction of multimodal corpora, efficient multimodal fusion, and vision-aware retrieval mechanisms for under-resourced translation and caption generation. Finally, the discussion turns to our ongoing explorations of retrieval-augmented generation (RAG) and the development of custom large language models for multilingual understanding and generation in under-resourced languages.
Coffee Break
Contributed Sessions 1
Lunch
Contributed Sessions 2
Coffee Break
Contributed Sessions 3
Welcome Party
Registration
Invited Lectures
Chairman
- Maxim Rybachuk (Financial University, Russia)
Vladimer Papava
(Tbilisi, Georgia)
Prof. Dr. Vladimer Papava,
Tbilisi State University, Georgia
ON THE THEORY OF TECHNOLOGICAL REGRESSION OF THE ECONOMY: NECROECONOMICS, ZOMBIE-ECONOMICS, RETROECONOMICS, AND SANCTIONOMICS
The theory of economic progress has been extensively developed by leading economists, including Joseph Schumpeter, Robert Solow, Robert Lucas, and Douglass North. By contrast, a systemic theory of economic regression remains in its formative stage. One important dimension of economic regression is technological decline within the economy. The presentation examines four distinct theoretical approaches to the issue of technological regression: necroeconomy (as a legacy of the command economy), zombie-economy (as an outcome of financial crises), retroeconomy (coming from a global tendency toward the use of outdated technologies), and sanctionomy, reflecting constraints on access to advanced technologies under economic sanctions. The presentation proposes an effective mechanism for overcoming necroeconomics, zombie-economics, and retroeconomics, grounded in a fundamental reform of bankruptcy legislation. In the case of sanctionomics, it assesses the effectiveness of economic sanctions, and demonstrates that the persistence of informal or illegal forms of globalization creates tangible opportunities to circumvent them.
Sankar Kumar Roy
(Midnapore, India)
Prof. Dr. Sankar Kumar Roy,
Department of Applied Mathematics, Vidyasagar University, India
ROBUST MULTI-OBJECTIVE OPTIMIZATION OF OMNICHANNEL CLOSED-LOOP FOOD SUPPLY CHAINS WITH BLOCKCHAIN, IOT,
AND BIOFUEL INTEGRATION
Food supply chains today are no longer linear—they are complex, data-rich, and increasingly circular. This necessitates integrated, technology-driven frameworks to achieve efficiency and sustainability. This talk asks a simple but critical question: how can we redesign the closed-loop food supply chain to be both intelligent and sustainable? In connection with the question, we would learn how to investigate the synergistic deployment of omnichannel strategies, Internet of Things (IoT)-enabled RFID systems, and blockchain technology to enhance traceability, operational transparency, and decision-making across the network. A closed-loop perspective is adopted, emphasizing the value of food waste into biofuel to simultaneously address waste management and renewable energy generation, thereby reducing carbon emissions. To capture system dynamics, a multi-period, bi-objective optimization model is formulated under uncertainty, incorporating robust optimization techniques for demand, supply, and process variability. The proposed model is solved using an ε-constraint method to generate Pareto-efficient solutions balancing economic and environmental objectives, followed by TOPSIS-based ranking to identify preferred strategies.Computational experiments across multiple instances, supported by sensitivity analysis, demonstrate that the integration of omnichannel logistics with IoT and blockchain significantly improves supply chain resilience, sustainability performance, and operational efficiency. The findings offer both theoretical advancement and actionable insights for designing next-generation sustainable food supply networks.
Coffee Break
Contributed Sessions 4
Lunch
Contributed Sessions 5
Coffee Break
Contributed Sessions 6
Conference Dinner
Registration
Invited Lectures
Chairman
- Maxim Rybachuk (Financial University, Russia)
Vladimer Papava
(Tbilisi, Georgia)
Prof. Dr. Vladimer Papava,
Tbilisi State University, Georgia
ON THE THEORY OF TECHNOLOGICAL REGRESSION OF THE ECONOMY: NECROECONOMICS, ZOMBIE-ECONOMICS, RETROECONOMICS, AND SANCTIONOMICS
The theory of economic progress has been extensively developed by leading economists, including Joseph Schumpeter, Robert Solow, Robert Lucas, and Douglass North. By contrast, a systemic theory of economic regression remains in its formative stage. One important dimension of economic regression is technological decline within the economy. The presentation examines four distinct theoretical approaches to the issue of technological regression: necroeconomy (as a legacy of the command economy), zombie-economy (as an outcome of financial crises), retroeconomy (coming from a global tendency toward the use of outdated technologies), and sanctionomy, reflecting constraints on access to advanced technologies under economic sanctions. The presentation proposes an effective mechanism for overcoming necroeconomics, zombie-economics, and retroeconomics, grounded in a fundamental reform of bankruptcy legislation. In the case of sanctionomics, it assesses the effectiveness of economic sanctions, and demonstrates that the persistence of informal or illegal forms of globalization creates tangible opportunities to circumvent them.
Sankar Kumar Roy
(Midnapore, India)
Prof. Dr. Sankar Kumar Roy,
Department of Applied Mathematics, Vidyasagar University, India
ROBUST MULTI-OBJECTIVE OPTIMIZATION OF OMNICHANNEL CLOSED-LOOP FOOD SUPPLY CHAINS WITH BLOCKCHAIN, IOT,
AND BIOFUEL INTEGRATION
Food supply chains today are no longer linear—they are complex, data-rich, and increasingly circular. This necessitates integrated, technology-driven frameworks to achieve efficiency and sustainability. This talk asks a simple but critical question: how can we redesign the closed-loop food supply chain to be both intelligent and sustainable? In connection with the question, we would learn how to investigate the synergistic deployment of omnichannel strategies, Internet of Things (IoT)-enabled RFID systems, and blockchain technology to enhance traceability, operational transparency, and decision-making across the network. A closed-loop perspective is adopted, emphasizing the value of food waste into biofuel to simultaneously address waste management and renewable energy generation, thereby reducing carbon emissions. To capture system dynamics, a multi-period, bi-objective optimization model is formulated under uncertainty, incorporating robust optimization techniques for demand, supply, and process variability. The proposed model is solved using an ε-constraint method to generate Pareto-efficient solutions balancing economic and environmental objectives, followed by TOPSIS-based ranking to identify preferred strategies.Computational experiments across multiple instances, supported by sensitivity analysis, demonstrate that the integration of omnichannel logistics with IoT and blockchain significantly improves supply chain resilience, sustainability performance, and operational efficiency. The findings offer both theoretical advancement and actionable insights for designing next-generation sustainable food supply networks.
Coffee Break
Contributed Sessions 4
Lunch
Contributed Sessions 5
Coffee Break
Contributed Sessions 6
Conference Dinner
Registration
Invited Lectures
Chairman
- Nilufar Abdurakhmonova (National University of Uzbekistan, Uzbekistan)
Vladimir Mazalov
(St. Peterburg, Russia)
Prof. Dr. Vladimir Mazalov,
St. Peterburg State University, Russia
ALTRUISTIC BEHAVIOR IN GAME-THEORETIC ENVIRONMENTAL MODELS
We consider a game-theoretic environmental model described by a differential game with an infinite horizon. The traditional approach is that players are rational and use selfish behavior that maximizes their personal winnings. But the selfish behavior of the players can have a negative impact on the environment. The reason is the limited supply of resources, which is influenced by all players (the tragedy of communs). We propose the concept of altruistic equilibrium in a differential game related to environmental issues and compare them with the Nash equilibrium. We assume that the players are connected by some network structure. According to the concept of altruistic equilibrium, players can offset a portion of other players' related payoffts with a portion of their own profits. We conduct numerical simulations and demonstrate the effectiveness of this approach in solving problems related to the use of natural resources related to the exploitation of natural resources.
Lina Volodzkienė
(Vilnius, Lithuania)
Prof. Dr. Lina Volodzkienė,
Faculty of Public Governance and Business, Mykolas Romeris University, Lithuania
STRENGTHENING HUMAN AND SOCIETAL RESILIENCE IN UNCERTAIN TIMES
Recent crises have shown that the same shock can have very different consequences across societies. Some recover relatively quickly, while others face lasting losses in human development, widening inequalities, and new forms of vulnerability. These differences cannot be explained by economic prosperity alone. They raise a broader question of resilience: what enables societies not only to withstand disruption, but also to adapt, learn, and continue developing when uncertainty persists? This question is becoming increasingly important as multiple overlapping crises reinforce one another. Under such conditions, resilience depends not only on economic resources, but also on human capabilities and opportunities, access to essential services, social cohesion, and the capacity of institutions to respond to change. Comparative analysis of country clusters shows that resilience is not evenly distributed. Yet the findings also show that being more developed does not automatically mean being more resilient. Inequality changes this picture considerably: when differences in the distribution of health, education, and income are taken into account, the actual gains in human development are significantly reduced, particularly in less developed country groups. At the same time, countries with the highest levels of human development tend to place greater pressure on the planet. This reveals an important paradox: development can strengthen the capacity to cope with some shocks while creating new vulnerabilities and risks for the future. These findings point to resilience as a capacity that is built over time rather than activated only when a crisis occurs. This also changes the role of public policy. Policy cannot focus only on managing the consequences of crises; it needs to create the conditions for resilience before crises occur by addressing the foundational vulnerabilities outlined above. The challenge is not to eliminate uncertainty, but to prevent it from repeatedly turning into lasting human and societal vulnerability.
Coffee Break
Contributed Sessions 7
Lunch
Discussion
Conclusions & Closing Ceremony Farewell Party
Excursion
Registration
Invited Lectures
Chairman
- Nilufar Abdurakhmonova (National University of Uzbekistan, Uzbekistan)
Vladimir Mazalov
(St. Peterburg, Russia)
Prof. Dr. Vladimir Mazalov,
St. Peterburg State University, Russia
ALTRUISTIC BEHAVIOR IN GAME-THEORETIC ENVIRONMENTAL MODELS
We consider a game-theoretic environmental model described by a differential game with an infinite horizon. The traditional approach is that players are rational and use selfish behavior that maximizes their personal winnings. But the selfish behavior of the players can have a negative impact on the environment. The reason is the limited supply of resources, which is influenced by all players (the tragedy of communs). We propose the concept of altruistic equilibrium in a differential game related to environmental issues and compare them with the Nash equilibrium. We assume that the players are connected by some network structure. According to the concept of altruistic equilibrium, players can offset a portion of other players' related payoffts with a portion of their own profits. We conduct numerical simulations and demonstrate the effectiveness of this approach in solving problems related to the use of natural resources related to the exploitation of natural resources.
Lina Volodzkienė
(Vilnius, Lithuania)
Prof. Dr. Lina Volodzkienė,
Faculty of Public Governance and Business, Mykolas Romeris University, Lithuania
STRENGTHENING HUMAN AND SOCIETAL RESILIENCE IN UNCERTAIN TIMES
Recent crises have shown that the same shock can have very different consequences across societies. Some recover relatively quickly, while others face lasting losses in human development, widening inequalities, and new forms of vulnerability. These differences cannot be explained by economic prosperity alone. They raise a broader question of resilience: what enables societies not only to withstand disruption, but also to adapt, learn, and continue developing when uncertainty persists? This question is becoming increasingly important as multiple overlapping crises reinforce one another. Under such conditions, resilience depends not only on economic resources, but also on human capabilities and opportunities, access to essential services, social cohesion, and the capacity of institutions to respond to change. Comparative analysis of country clusters shows that resilience is not evenly distributed. Yet the findings also show that being more developed does not automatically mean being more resilient. Inequality changes this picture considerably: when differences in the distribution of health, education, and income are taken into account, the actual gains in human development are significantly reduced, particularly in less developed country groups. At the same time, countries with the highest levels of human development tend to place greater pressure on the planet. This reveals an important paradox: development can strengthen the capacity to cope with some shocks while creating new vulnerabilities and risks for the future. These findings point to resilience as a capacity that is built over time rather than activated only when a crisis occurs. This also changes the role of public policy. Policy cannot focus only on managing the consequences of crises; it needs to create the conditions for resilience before crises occur by addressing the foundational vulnerabilities outlined above. The challenge is not to eliminate uncertainty, but to prevent it from repeatedly turning into lasting human and societal vulnerability.
Coffee Break
Contributed Sessions 7
Lunch
Discussion
Conclusions & Closing Ceremony Farewell Party
Excursion
ВАЖНЫЕ ДАТЫ
Описание | Даты |
Начало регистрации: | – 15 сентября 2025 г. |
Крайний срок для предложений по организации секций: | – 20 марта 2026 г. |
Регистрация и подача аннотаций докладов для сборника трудов Springer Proceedings: | – 20 апреля 2026 г. |
Подача статьи в сборник трудов Springer Proceedings: | – 25 мая 2026 г. |
Уведомление о принятии статей к публикации: | – 15 июня 2026 г. |
Ранняя регистрация (оплата оргвзноса со скидкой): | – 08 сентября 2026 г. |
Регистрация и подача аннотаций докладов без публикации в сборнике трудов Springer Proceedings: | – 12 сентября 2026 г. |
Конференция: | – 23-25 сентября 2026 г. |
Подача статей в высокорейтинговые журналы: | – 25 февраля 2027 г. |
ТАРИФНЫЕ ПЛАНЫ*
Очное участие
€45
- Пакет материалов конференции
- Сборник аннотаций докладов конференции
- Доступ в залы на все заседания конференции
- Кофе-брейк, обед, приветственная вечеринка
Студенты
€20
- Пакет материалов конференции
- Сборник аннотаций докладов конференции
- Доступ в залы на все заседания конференции
- Кофе-брейк, обед, приветственная вечеринка
Заочное участие
€30
- Сборник аннотаций
докладов конференции
в электронном
виде - Доступ ко всем
заседаниям
конференции
на платформе
Zoom
Очное участие
€60
- Пакет материалов конференции
- Сборник аннотаций докладов конференции
- Доступ в залы на все заседания конференции
- Кофе-брейк, обед, приветственная вечеринка
Студенты
€30
- Пакет материалов конференции
- Сборник аннотаций докладов конференции
- Доступ в залы на все заседания конференции
- Кофе-брейк, обед, приветственная вечеринка
Заочное участие
€40
- Сборник аннотаций
докладов конференции
в электронном
виде - Доступ ко всем
заседаниям
конференции
на платформе
Zoom
ВАЖНО! Оплата организационного взноса осуществляется в национальной валюте по официальному курсу страны.
ИНФОРМАЦИЯ О ПУБЛИКАЦИЯХ
We encourage researchers who are starting or developing their research related to computing and OR in social sciences to present their work for discussion and take part in the tutorials on the challenging topics of modelling and simulation of social-behavioural phenomena in creative societies.
Contributors can opt to participate in the conference with or without a paper for Proceedings. In case of without a paper for Proceedings, just an abstract of the talk is required. In case of with a paper for Proceedings, a short paper is required. The Proceedings of the conference will be published in Springer Conference Proceedings Series “Communications in Computer and Information Science” (CCIS).
The submitted articles should be 12-15+ pages long. Much shorter papers (6-11 pages long) will be accepted too, but only as an exception.
Please, use the following guidelines, template when preparing the article (in Word or Latex) and fill out the Licence to Publish form for CCIS.
We expect to receive the articles by May 25, 2026. Each submitted article will be rigorously evaluated by assessing the originality, significance, technical soundness, clarity of exposition, and relevance to the issue’s theme. Only the papers that meet these criteria will be accepted.
The acceptance of the articles will be announced by June 15, 2026. Payment of the registration fee is a requirement for the publication of an article.
The volume of MSBC-2026 Springer Conference Proceedings in series “Communications in Computer and Information Science” will be delivered for participants during the conference.
Participants can submit full papers on the conference topics for publication in Special Issues of Journal of Operations Research Society of China or Mathematics.
In addition to the conference Proceedings and a special issue in the post-conference journal, a collective monograph on the subject of the conference topics will be published by a worldwide publisher. The title and content of the book will be announced before the conference.
РЕГИСТРАЦИЯ
К участию в конференции приглашаются участники не только из академических кругов, но и из различных сфер бизнеса, про-мышленности и организаций, занимающихся вычислениями в социальных и гуманитарных науках, системным моделированием и пространственно-временным анализом в экономике. Участники получат возможность связаться с ведущими экспертами, узнать о последних достижениях и новых инструментах, появившихся в тематических областях работы конференции.
Если вы планируете участвовать в конференции или хотите организовать свою секцию (приглашенную сессию) в рамках конференции, пожалуйста, заполните одну из следующих форм.
АДРЕС ПРОВЕДЕНИЯ
Национальный университет Узбекистана
имени Мирзо Улугбека
ул. Университетская, д. 4,
г. Ташкент, Республика Узбекистан
100174
г. Ташкент, Республика Узбекистан
100174