Decision Support Systems and AI-Driven Optimization for Engineering, Healthcare, and Management
This special issue aims to present state-of-the-art research on the integration of Decision Support Systems (DSS) and AI-driven optimization techniques in solving complex problems across engineering, healthcare, and management domains.
Unlike traditional studies focused on a single method or sector, the issue highlights the synergy between mathematical modeling, machine learning, and multi-criteria decision-making in diverse and impactful applications such as emergency planning, healthcare diagnostics, sustainability, and resource allocation. With a balance of theoretical depth and real-life case studies, this collection will offer readers new ideas, tools, and inspiration to push the boundaries of what decision support and AI can do—making it a valuable contribution to the field.
Topics of Interest
In today’s rapidly evolving world, organizations face increasingly complex decision-making environments driven by uncertainty, data abundance, and the need for efficiency and sustainability. This has led to a growing interest in combining Decision Support Systems (DSS) with AI-driven optimization techniques to support better, faster, and more informed decisions across fields such as engineering, healthcare, and management. Recent studies and citation trends highlight a clear shift toward interdisciplinary solutions that integrate machine learning, optimization, and decision sciences.
Themes and Key Features
- AI-Driven Optimization Techniques: Application of machine learning, deep learning, and heuristic methods in solving complex optimization problems across domains.
- Decision Support Systems (DSS): Development and implementation of intelligent systems to support data-driven, multi-criteria, and strategic decision-making processes.
- Interdisciplinary Applications: Real-world case studies in engineering, healthcare, logistics, energy, and management showcasing the integration of AI and DSS.
- Sustainable and Resilient Solutions: Research that contributes to sustainability, resource efficiency, risk management, and alignment with UN SDGs.
- Hybrid and Integrated Approaches: Novel methodologies that combine optimization models with AI, simulation, and decision analysis frameworks to improve decision quality and adaptability.
Submission Information
Submissions are made using ScholarOne Manuscripts. Registration and access are available here https://mc.manuscriptcentral.com/ijicc
Author guidelines must be strictly followed. Please see here
Key Dates
Closing date for submissions: 28th December 2025
For more details refer here
