Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in AI-Driven Modeling, Intelligent Optimization, and Interdisciplinary Applications
HMMOCS-V 2026: advancing hybrid intelligence for complex systems
As complex systems become smarter, more connected, and data-driven, innovative solutions are essential to address emerging challenges. HMMOCS-V 2026 brings together researchers and experts to explore the latest advances in hybrid modeling, artificial intelligence, intelligent optimization, digital twins, and adaptive systems. Join an international community shaping the next generation of intelligent technologies and interdisciplinary solutions.
As complex systems become smarter, more connected, and data-driven, innovative solutions are essential to address emerging challenges. HMMOCS-V 2026 brings together researchers and experts to explore the latest advances in hybrid modeling, artificial intelligence, intelligent optimization, digital twins, and adaptive systems. Join an international community shaping the next generation of intelligent technologies and interdisciplinary solutions.
About the workshop
Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in AI-Driven Modeling, Intelligent Optimization, and Interdisciplinary Applications
We invite researchers, scientists, and practitioners to participate in the V International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-V 2026), which will take place 2-4 December 2026 at Bukhara State University, Uzbekistan.
We invite researchers, scientists, and practitioners to participate in the V International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-V 2026), which will take place 2-4 December 2026 at Bukhara State University, Uzbekistan.
The workshop aims to bring together experts working on innovative approaches to modeling, analysis, and optimization of complex systems. We welcome original contributions presenting theoretical developments, computational methods, and practical applications.
Topics of interest include:
As part of the workshop, we are currently accepting research papers for the edited volume “Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in AI-Driven Modeling, Intelligent Optimization, and Interdisciplinary Applications,” proposed for publication in the Lecture Notes in Networks and Systems series.
Selected papers are planned for inclusion in the conference proceedings, with publication proposed in the internationally recognized Lecture Notes in Networks and Systems series. This publication platform covers a wide range of topics, including cyber-physical systems, intelligent and autonomous systems, distributed networks, digital twins, control and energy systems, intelligent manufacturing, computational optimization, and other areas related to modern networked and intelligent technologies. The series provides international visibility and worldwide dissemination of research results.
Researchers from academia, research institutes, and industry are warmly invited to contribute their latest findings and participate in this international scientific event.
Submission deadline: 31 December 2026
Join us in advancing research on hybrid modeling, artificial intelligence, and intelligent optimization of complex systems and in fostering international collaboration in this rapidly developing field.
Topics of interest include:
- Hybrid modeling and intelligent optimization
- Artificial intelligence and machine learning
- Intelligent decision support systems
- Cyber-physical and distributed intelligent systems
- Digital twins and computational simulation
- Data mining, multimodal analytics, and pattern recognition
- Adaptive intelligence and evolutionary computation
- Interdisciplinary applications of modeling and optimization
As part of the workshop, we are currently accepting research papers for the edited volume “Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in AI-Driven Modeling, Intelligent Optimization, and Interdisciplinary Applications,” proposed for publication in the Lecture Notes in Networks and Systems series.
Selected papers are planned for inclusion in the conference proceedings, with publication proposed in the internationally recognized Lecture Notes in Networks and Systems series. This publication platform covers a wide range of topics, including cyber-physical systems, intelligent and autonomous systems, distributed networks, digital twins, control and energy systems, intelligent manufacturing, computational optimization, and other areas related to modern networked and intelligent technologies. The series provides international visibility and worldwide dissemination of research results.
Researchers from academia, research institutes, and industry are warmly invited to contribute their latest findings and participate in this international scientific event.
Submission deadline: 31 December 2026
Join us in advancing research on hybrid modeling, artificial intelligence, and intelligent optimization of complex systems and in fostering international collaboration in this rapidly developing field.
Guest editors and international committee
Meet the distinguished scholars guiding HMMOCS-V 2026 and shaping its scientific program.
- Predrag StanimirovićGuest editorUniversity of Niš, Serbia
- Spyridon MourtasGuest editorNational and Kapodistrian University of Athens, Greece
- Jajati Keshari SahooGuest editorBITS Pilani, India
Hijaz Ahmad, Section of Mathematics, International Telematic University Uninettuno, Roma, Italy
Dijana Mosic, University of Niš, Faculty of Sciences and Mathematics, Niš, Serbia
Oleg Kravets, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Igor Kovalev, Department of Informatics, Siberian Federal University, Russia
Roman Sergienko, Riskmethods GmbH, Munich, Germany
Mirzo Sharipov, Bukhara State University, Bukhara, Uzbekistan
Saule Sakipova, Karaganda University named after academician E.A. Buketov, Kazakhstan
Dilshod Kholmatov, University of Business and Science, Namangan, Uzbekistan
Sharofzoda Razzoq, Research Institute for Sustainable Development and Green Economy, International University of Tourism and Entrepreneurship of Tajikistan, Dushanbe, Tajikistan
Dijana Mosic, University of Niš, Faculty of Sciences and Mathematics, Niš, Serbia
Oleg Kravets, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Igor Kovalev, Department of Informatics, Siberian Federal University, Russia
Roman Sergienko, Riskmethods GmbH, Munich, Germany
Mirzo Sharipov, Bukhara State University, Bukhara, Uzbekistan
Saule Sakipova, Karaganda University named after academician E.A. Buketov, Kazakhstan
Dilshod Kholmatov, University of Business and Science, Namangan, Uzbekistan
Sharofzoda Razzoq, Research Institute for Sustainable Development and Green Economy, International University of Tourism and Entrepreneurship of Tajikistan, Dushanbe, Tajikistan
Inmaculada Medina-Bulo, Universidad de Cádiz, Spain
Ivan Rozhnov, Siberian Federal University, Russia
Akbar Abrorov, Bukhara State Technical University, Uzbekistan
Aleksei Vakhnin, University of Eastern Finland, Finland
Jajati Keshari Sahoo, BITS Pilani-K.K Birla Goa Campus, Goa, India
Ratikanta Behera, Indian Institute of Science Bangalore, Bangalore, Karnataka, India
Dijana Mosic, University of Nis, Faculty of Sciences and Mathematics, Nis, Serbia
Sharof Rakhimov, Bukhara State Pedagogical Institute, Uzbekistan
Akramjon Nurmatov, University of Business and Science, Namangan, Uzbekistan
Maksat Kalimoldayev, Institute of Information and Computational Technologies, Kazakhstan
Ivan Rozhnov, Siberian Federal University, Russia
Akbar Abrorov, Bukhara State Technical University, Uzbekistan
Aleksei Vakhnin, University of Eastern Finland, Finland
Jajati Keshari Sahoo, BITS Pilani-K.K Birla Goa Campus, Goa, India
Ratikanta Behera, Indian Institute of Science Bangalore, Bangalore, Karnataka, India
Dijana Mosic, University of Nis, Faculty of Sciences and Mathematics, Nis, Serbia
Sharof Rakhimov, Bukhara State Pedagogical Institute, Uzbekistan
Akramjon Nurmatov, University of Business and Science, Namangan, Uzbekistan
Maksat Kalimoldayev, Institute of Information and Computational Technologies, Kazakhstan
Spyridon Mourtas, National and Kapodistrian University of Athens, Greece
Stefan Stanimirović, University of Niš, Serbia
Roman Kuzmich, Siberian Federal University, Russia
Komil Astanakulov, NRU TIIAME, Tashkent, Uzbekistan
Vadim Tynchenko, Bauman University, Moscow, Russia
Tulkin Rasulov, Bukhara State University, Uzbekistan
Kudayberdi Kozhobekov, Osh State University, Kyrgyzstan
En. Mohd Zamri Ibrahim, Management and Science University, Malaysia
Asrorzoda Sattor, International University of Tourism and Entrepreneurship of Tajikistan, Dushanbe, Tajikistan
Suklyun Hong, Sejong University, South Korea
Stefan Stanimirović, University of Niš, Serbia
Roman Kuzmich, Siberian Federal University, Russia
Komil Astanakulov, NRU TIIAME, Tashkent, Uzbekistan
Vadim Tynchenko, Bauman University, Moscow, Russia
Tulkin Rasulov, Bukhara State University, Uzbekistan
Kudayberdi Kozhobekov, Osh State University, Kyrgyzstan
En. Mohd Zamri Ibrahim, Management and Science University, Malaysia
Asrorzoda Sattor, International University of Tourism and Entrepreneurship of Tajikistan, Dushanbe, Tajikistan
Suklyun Hong, Sejong University, South Korea
Publication opportunity
Contribute to the upcoming publication on hybrid methods for complex systems.
Selected high-quality papers presented at the workshop will be published in the Lecture Notes in Networks and Systems (LNNS) series.
Publication series
The LNNS series publishes peer-reviewed conference proceedings and edited volumes covering recent advances in systems science, artificial intelligence, networks, and computational technologies.
The series includes research in areas such as cyber-physical systems, autonomous systems, sensor networks, control and energy systems, robotics, smart manufacturing, transportation systems, and socio-economic systems. LNNS provides international visibility, rapid publication timelines, and wide global dissemination of scientific results through a recognized academic publishing platform.
The proceedings of the previous workshops in Lecture Notes in Networks and Systems:
The series includes research in areas such as cyber-physical systems, autonomous systems, sensor networks, control and energy systems, robotics, smart manufacturing, transportation systems, and socio-economic systems. LNNS provides international visibility, rapid publication timelines, and wide global dissemination of scientific results through a recognized academic publishing platform.
The proceedings of the previous workshops in Lecture Notes in Networks and Systems:
- Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving, LNNS, volume 1481 - https://link.springer.com/book/10.1007/978-3-031-95649-2
- Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving, Volume 1, LNNS, volume 1944 - https://link.springer.com/book/10.1007/978-3-032-24402-4
- Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving, Volume 2, LNNS, volume 2040 - https://link.springer.com/book/9783032301031
Exploring innovative hybrid approaches that integrate mathematical modeling, artificial intelligence, and intelligent optimization to address the challenges of complex and interconnected systems.
Scope of the Workshop
analyzing, and optimizing complex systems across science, engineering, technology, and society. It emphasizes the integration of mathematical methods, artificial intelligence, machine learning, and computational intelligence to develop effective solutions for dynamic, nonlinear, and data-intensive environments. Particular attention is given to hybrid and data-driven modeling, intelligent and multicriteria optimization, decision-making under uncertainty, cyber-physical systems, digital twins, and advanced computational simulation. The workshop also addresses scalable computational approaches, intelligent monitoring and control, distributed and multi-agent systems, and emerging technologies for analyzing and optimizing large-scale interconnected systems.
The scientific scope further encompasses data mining, deep learning, multimodal analytics, computer vision, pattern recognition, and knowledge discovery, alongside adaptive intelligence, evolutionary and bio-inspired computation, reinforcement learning, and explainable and trustworthy artificial intelligence. Special emphasis is placed on combining analytical models with data-driven techniques to improve forecasting, risk assessment, intelligent decision support, and system performance. The workshop encourages interdisciplinary research and practical applications in industry, manufacturing, energy, transportation, agriculture, environmental engineering, finance, healthcare, and education. By bringing together researchers and practitioners from diverse disciplines, HMMOCS-V 2026 aims to foster international collaboration and advance innovative, scalable, and sustainable solutions to real-world challenges.
The scientific scope further encompasses data mining, deep learning, multimodal analytics, computer vision, pattern recognition, and knowledge discovery, alongside adaptive intelligence, evolutionary and bio-inspired computation, reinforcement learning, and explainable and trustworthy artificial intelligence. Special emphasis is placed on combining analytical models with data-driven techniques to improve forecasting, risk assessment, intelligent decision support, and system performance. The workshop encourages interdisciplinary research and practical applications in industry, manufacturing, energy, transportation, agriculture, environmental engineering, finance, healthcare, and education. By bringing together researchers and practitioners from diverse disciplines, HMMOCS-V 2026 aims to foster international collaboration and advance innovative, scalable, and sustainable solutions to real-world challenges.
Advancing hybrid modeling, AI-driven computational methods, and intelligent optimization to develop adaptive, data-driven solutions for complex and interconnected systems.
Research focus
The workshop highlights recent research advances in hybrid mathematical and computational modeling, artificial intelligence, machine learning, and intelligent optimization for addressing complex scientific and engineering challenges. Contributions focus on integrating theoretical methods with data-driven approaches, developing scalable optimization algorithms, and enhancing decision-making under uncertainty in dynamic and interconnected environments.
Key research directions include AI-driven and cyber-physical systems, digital twins, computational simulation, intelligent monitoring and control, and distributed and multi-agent technologies. Particular attention is given to data mining, deep learning, multimodal analytics, computer vision, and pattern recognition, as well as their applications in knowledge discovery, forecasting, and predictive modeling.
Additional emphasis is placed on adaptive intelligence, evolutionary and bio-inspired computation, reinforcement learning, neural networks, and explainable and trustworthy AI. The workshop encourages interdisciplinary research that combines innovative computational methodologies with practical applications in industry, manufacturing, energy, transportation, finance, healthcare, and environmental systems, promoting intelligent, efficient, and sustainable solutions to real-world challenges.
Key research directions include AI-driven and cyber-physical systems, digital twins, computational simulation, intelligent monitoring and control, and distributed and multi-agent technologies. Particular attention is given to data mining, deep learning, multimodal analytics, computer vision, and pattern recognition, as well as their applications in knowledge discovery, forecasting, and predictive modeling.
Additional emphasis is placed on adaptive intelligence, evolutionary and bio-inspired computation, reinforcement learning, neural networks, and explainable and trustworthy AI. The workshop encourages interdisciplinary research that combines innovative computational methodologies with practical applications in industry, manufacturing, energy, transportation, finance, healthcare, and environmental systems, promoting intelligent, efficient, and sustainable solutions to real-world challenges.
Submit your research
Share your insights on hybrid modeling, AI, and optimization. Contribute to the advancement of complex systems analysis.
Manuscript guidelines
Please ensure that your manuscript aligns with our specific formatting guidelines as well as our detailed publication requirements to avoid any issues during the submission process.
- Content and Structure
- Thematic relevance: The article must correspond to one of the announced topics of the collection.
- Language: Articles are published in English. Submissions are accepted in English or Russian (articles in Russian will be translated into English for an additional fee of 9,000 rubles).
- Structure: Mandatory sections include: Introduction, Materials and Methods, Results, Discussion, and Conclusion. A Acknowledgments section may be included if necessary.
- Length: Minimum 10–12 pages in the publisher’s template, excluding the bibliography. Illustrations and tables should not exceed 25% of the total article length.
- Authorship: Recommended number of authors is no more than 5.
- Information content: The article should contain elements of informatics or mathematics (models, schemes, approaches, logical diagrams, programming languages, cryptography, architectures, etc.).
- Article Length Requirements
- The recommended length of a manuscript for publication in Lecture Notes in Networks and Systems is generally at least 30,000 characters including spaces.
- Articles shorter than 20,000 characters including spaces will not be considered for publication.
- The article length includes main text, tables, and figures, but excludes bibliography, title page, and abstract.
- This requirement helps ensure sufficient scientific depth and topic coverage to meet the standards of international scientific publications of this class.
- Formatting and Style
- File format: Microsoft Word.
- Formatting: Use the publisher’s template (see the template and instructions). Formatting by editors is a paid service (2,800 rubles).
- Illustrations: Diagrams and tables are allowed but must be within the text boundaries.
- Abstract: Minimum 100 words, maximum 200 words.
- Bibliography: Minimum of 10 references, primarily articles from international journals.
- Citations: Self-citations and citations of individual authors should not exceed one citation per author.
- Paper Template
- Originality and Ethics
- Originality: At least 85% originality (excluding the bibliography).
- Plagiarism: All articles undergo mandatory plagiarism checks using iThenticate. Please refer to the “Originality Check” section.
- Peer Review: Double-blind peer review is applied.
- License Agreement: All authors must read and sign the license agreement, which is submitted as a PDF after acceptance.
- Third-party Content: Third-party content is any material in the manuscript that is not your original work. This includes text fragments, images, photos, poems, song lyrics, screenshots, etc. These may be found in various sources including but not limited to internet, printed and online books and articles, dissertations, reports, conference materials, photocopies, educational packages, and translations. Special attention should be paid to sensitive images featuring recognizable faces, logos, brands/trademarks, agency or internet images, as well as textual content such as song lyrics, poems, interviews, social media content, and references to commercial organizations. When third-party content is used, permission for its use must be provided (permission form is available in the “Templates” section).
- Bibliography Requirements
- Each author should be cited only once, regardless of their authorship status.
- No more than one citation per edition is allowed.
- The publisher discourages citations of publications from the same publisher.
- The abbreviation “et al.” is prohibited for hiding author names; a full list of all authors must be provided for every reference.
- Bibliographic entries must include surnames and initials of all authors, regardless of number.
- References should be complete and accurate, containing all necessary information to identify the source.
- The bibliography must include only sources that are directly cited or mentioned in the text.
- Relevant and up-to-date sources related to the research topic are recommended.
- If available, please include the DOI (Digital Object Identifier) for each article.
- Formatting of the bibliography should follow the citation style accepted by the publication.
- Review ProcessAll submitted manuscripts will undergo a double-blind peer review process to ensure high scientific quality and relevance to the workshop topics. Each paper will be evaluated by independent reviewers with expertise in the relevant research area.
The review process will assess originality, methodological rigor, technical quality, clarity of presentation, and relevance to hybrid methods for modeling and optimization of complex systems. Authors may be asked to revise their manuscripts based on reviewers’ comments.
Only papers that successfully pass the peer-review process and meet the publication standards of the Lecture Notes in Networks and Systems (LNNS) series will be accepted for inclusion in the workshop proceedings.
Get in touch
Akbar Abrorov
E-mail: abrorovas@univers.uz
+998 90-611-50-05 (whats up, viber, telegram)
Bukhara State University, Main Building, Bukhara, Uzbekistan
E-mail: abrorovas@univers.uz
+998 90-611-50-05 (whats up, viber, telegram)
Bukhara State University, Main Building, Bukhara, Uzbekistan
