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.
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.
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:
  • 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
We especially encourage interdisciplinary research and innovative approaches that integrate artificial intelligence, data-driven methods, mathematical modeling, computational intelligence, and optimization techniques to address complex challenges in science, engineering, industry, and society.

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 Stanimirović
    Guest editor
    University of Niš, Serbia
  • Spyridon Mourtas
    Guest editor
    National and Kapodistrian University of Athens, Greece
  • Jajati Keshari Sahoo
    Guest editor
    BITS 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
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
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
Publication opportunity
Contribute to the upcoming publication on hybrid methods for complex systems.

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
The workshop focuses on theoretical, computational, and interdisciplinary advances in modeling, 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, cyber-physical systems, digital twins, and advanced computational simulation. The workshop also explores intelligent decision support, distributed and multi-agent systems, multimodal data analytics, pattern recognition, adaptive intelligence, and evolutionary computation.

Selected high-quality papers presented at the workshop will be published in the Lecture Notes in Networks and Systems (LNNS) 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 workshop were published in the volume Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving, included in Lecture Notes in Networks and Systems, Volume 1481 (2025).
Volume 1481 (2025)
The workshop emphasizes recent research developments in advanced computational and analytical methods for complex problem solving. Contributions focus on innovative applications of artificial intelligence, machine learning, mathematical modeling, and adaptive optimization techniques.

Research focus
The research contributions concentrate on the development and application of advanced computational methods for complex problem solving. Key themes include artificial intelligence applications in real-world systems, interdisciplinary mathematical modeling, data mining and machine learning techniques, and pattern recognition in large datasets. Additional emphasis is placed on adaptive intelligence, including evolutionary algorithms and neural network learning mechanisms, as well as innovative optimization strategies for dynamic, distributed, and data-rich systems.
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 Process
    All 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