Aim and Scope
Metaheuristic Optimization Review is an international, peer-reviewed journal dedicated to publishing high-quality review-oriented scholarship in the field of metaheuristic optimization and related intelligent optimization methods. The journal provides a platform for systematic reviews, survey papers, bibliometric analyses, tutorial articles, and critical perspective papers that synthesize current knowledge, evaluate methodological developments, and identify emerging research directions in optimization.
The journal focuses on the analysis, comparison, and assessment of metaheuristic and nature-inspired optimization approaches, including their theoretical foundations, algorithmic developments, benchmarking practices, and practical applications. Emphasis is placed on review contributions that provide clear scholarly value through critical evaluation, structured synthesis, methodological insight, and guidance for future research.
Metaheuristic Optimization Review welcomes manuscripts that examine optimization methods such as swarm intelligence, evolutionary computation, hybrid metaheuristics, population-based search, and related intelligent optimization frameworks. The journal also considers review-based contributions in adjacent domains, including machine learning, intelligent systems, robotics, software engineering, natural language processing, and multi-agent systems, where metaheuristic optimization constitutes a central methodological component.
The journal is intended for researchers, academics, and practitioners seeking authoritative and up-to-date review resources on optimization methods and their applications across science, engineering, and computational intelligence.
Topics of interest include, but are not limited to:
Metaheuristic Optimization
Swarm Intelligence
Evolutionary Algorithms
Nature-Inspired Optimization Methods
Hybrid and Adaptive Metaheuristics
Benchmarking and Comparative Analysis of Optimization Algorithms
Optimization in Machine Learning and Data Analytics
Optimization in Software Engineering
Intelligent Robotics and Autonomous Systems
Optimization in Natural Language Processing
Multi-Agent and Distributed Optimization Systems
Applications of Metaheuristic Methods in Engineering and Computational Intelligence