Artificial Intelligence (AI) and Optimization in System-of-Systems Engineering for Resilient, Sustainable Communities
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 31
Special Issue Editors
Interests: system resilience; system restoration modeling; disaster management; supply chain and logistics; extended reality
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Communities around the world are facing unprecedented challenges related to climate change, infrastructure fragility, urbanization, and social inequities. Building resilient and sustainable communities requires coordinated efforts across interconnected systems, each governed by diverse stakeholders and operational constraints. These interconnected domains form a system-of-systems (SoS) environment, where complexity, uncertainty, and multi-objective trade-offs are the norm rather than the exception.
Recent advances in artificial intelligence (AI) and optimization techniques offer powerful tools to address the decision-making, design, and coordination challenges inherent in SoS engineering. From predictive analytics and reinforcement learning to multi-objective optimization and evolutionary computation, AI-based methods are increasingly capable of managing uncertainty, adapting to dynamic environments, and uncovering insights from vast data sources. When applied to project management, infrastructure planning, or policy evaluation, these techniques enable more effective resource allocation, scenario simulation, and risk mitigation.
This Special Issue invites the submission of high-quality, original research and review articles at the intersection of AI, optimization, and SoS engineering, with a specific focus on applications that advance the resilience, equity, and sustainability of communities. We are particularly interested in interdisciplinary approaches that integrate computational methods with domain knowledge in infrastructure systems, environmental planning, disaster resilience, project management, and community development.
Topics of interest include, but are not limited to the following:
- AI-enabled modeling and simulation of interdependent infrastructure systems;
- Optimization under uncertainty in SoS decision-making frameworks;
- Reinforcement learning and intelligent agents for adaptive infrastructure planning;
- Project management and governance of large-scale, SoS-driven initiatives;
- Digital twins and smart cities as platforms for resilience assessment;
- Equity-focused optimization in resource-constrained environments;
- Explainable and ethical AI for public-sector infrastructure decisions;
- Human–AI collaboration to achieve sustainable community planning.
By bringing together diverse contributions across disciplines, this Special Issue aims to provide a foundation for next-generation intelligent infrastructure systems that are not only technically robust but also socially responsive and environmentally sound.
Dr. Sudipta Chowdhury
Dr. Ammar Alzarrad
Guest Editors
Manuscript Submission Information
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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. Information 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 1800 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
- system-of-systems engineering
- sustainable infrastructure
- optimization under uncertainty
- smart cities
- digital twins
- adaptive decision support
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