AI-Driven Simulation and Optimization for Systems
A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Artificial Intelligence and Digital Systems Engineering".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 442
Special Issue Editors
Interests: systems and SoS approach; simulation-based optimization
Interests: non-industrial systems applications (emissions, finance, physics, etc.); IT technologies/platform to support AI
Special Issues, Collections and Topics in MDPI journals
Interests: AI-based optimization techniques; algorithms foundations
Interests: industrial systems applications; digital twins design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) has rapidly matured into a cornerstone of contemporary systems research, enabling unprecedented capabilities in simulation fidelity, predictive analytics, and optimization across engineering, socio-technical, ecological, and cyber-physical domains. The integration of AI techniques—including machine learning, deep learning, reinforcement learning, agentic, data-driven optimization—into systems simulation and decision-support frameworks is transforming how complex systems are understood, designed, operated, and controlled.
This Special Issue will provide a platform for researchers, practitioners, and policymakers to explore how AI can elevate systems simulation and optimization paradigms, through high-quality original research and comprehensive reviews. We encourage submissions that demonstrate novel algorithms, frameworks, and applications where AI enhances the realism, scalability, robustness, or efficiency of simulations and optimization processes to improve systems performance. Contributions should emphasize methodological innovation, rigorous evaluation, and relevance to real-world systems challenges.
Topics of interest include, but are not limited to:
- AI-enhanced simulation engines for complex dynamic systems
- Deep learning models for surrogate simulation and/or real-time prediction
- Reinforcement learning and adaptive control for system optimization
- Data-driven and multi-objective optimization under uncertainty
- Digital twins with embedded AI for real-time monitoring and decision support
- Multi-agent systems for distributed coordination and systems optimization
- Agentic AI architectures for autonomous simulation, planning, and optimization
- AI-based methods for sensitivity analysis, risk assessment, and scenario planning
- Integration of simulation outputs with AI-guided decision support
- Applications in manufacturing, logistics, energy systems, healthcare, supply chain, finance, and socio-technical infrastructures
Dr. Miguel Gutierrez
Prof. Dr. Joaquin Ordieres Meré
Dr. Marco Vannucci
Dr. Valentina Colla
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence (AI)
- complex systems optimization
- computational modeling
- simulation modeling
- reinforcement learning
- agentic AI
- multi-agent systems
- distributed decision-making
- digital twins
- data-driven optimization
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