Recent Advances in Artificial Intelligence and Metaheuristics Optimization
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 579
Special Issue Editors
Interests: operations research; artificial intelligence; transportation; simulation optimization
Special Issues, Collections and Topics in MDPI journals
Interests: swarm intelligence; optimization metaheuristics; machine learning; deep learning; computer vision; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
You are welcome to submit your manuscript to our Special Issue titled: “Recent Advances in Artificial Intelligence and Metaheuristics Optimization”.
Artificial Intelligence (AI) and metaheuristic optimization have emerged as two of the most transformative paradigms in computational science. While AI techniques—particularly machine learning and deep learning—enable data-driven learning and decision-making, metaheuristics provide powerful problem-solving mechanisms to optimize complex, high-dimensional, and nonlinear tasks. The fusion of these two domains is driving cutting-edge solutions across energy systems, healthcare, and cybersecurity, as well as transportation, industrial design, and sustainable development.
This Special Issue aims to gather original research contributions, novel applications, and comprehensive reviews on the integration of AI with metaheuristic optimization. We particularly welcome works that address theoretical foundations, hybrid frameworks, performance benchmarking, explainability, and real-world deployment. By fostering dialogue between AI and optimization communities, the issue seeks to highlight the latest advances and inspire new directions in research and practice.
Potential research areas include, but are not limited to the following:
- Novel Metaheuristic Algorithms: Design, theoretical analysis, and benchmarking of new swarm intelligence and evolutionary approaches.
- Hybrid AI–Metaheuristic Models: Integration of metaheuristics with machine learning, deep learning, reinforcement learning, and explainable AI.
- Hyperparameter Tuning and Model Selection: Advanced optimization strategies for neural networks, ensembles, and emerging AI architectures.
- Applications in Energy and Sustainability: Renewable energy forecasting, smart grids, battery health prediction, and green building optimization.
- Healthcare and Biomedical Systems: Disease diagnosis, medical imaging, personalized treatment, and bioinformatics.
- Cybersecurity and Critical Infrastructure: Intrusion detection, risk management, blockchain security, and anomaly detection.
- Big Data and Cloud/Edge Computing: Resource allocation, scheduling, federated learning, and distributed optimization.
- Trustworthy and Explainable AI: Robustness, interpretability, fairness, and ethical optimization frameworks.
Prof. Dr. Angel A. Juan
Dr. Nebojsa Bacanin
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. Algorithms 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
- metaheuristic optimization
- swarm intelligence
- hybrid AI models
- hyperparameter tuning
- machine learning
- sustainable applications
- explainable AI
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