Submission Deadline: 01 October 2025 View: 283 Submit to Special Issue
Assistant Prof. Rui Zhong
Email: zhongrui@iic.hokudai.ac.jp
Affiliation: Information Initiative Center, Hokkaido University, Sapporo, 060-0808, Japan
Research Interests: Evolutionary Computation, Metaheuristics, Hyper-heuristics
Assistant Prof. Jun Yu
Email: yujun@ie.niigata-u.ac.jp
Affiliation: Institute of Science and Technology, Niigata University, Niigata, 950-2181, Japan
Research Interests: Artificial Intelligence, Machine Learning, Deep Learning, Evolutionary Computation
Evolutionary algorithms (EAs) have become a cornerstone of optimization methodology, demonstrating remarkable versatility in addressing complex, high-dimensional, and nonlinear optimization problems across disciplines. From addressing real-world engineering challenges to exploring theoretical frontiers, EAs and their variants? Such as genetic algorithms, differential evolution, and swarm intelligence. Continue to expand the boundaries of problem-solving capabilities.
This Special Issue aims to unite innovative contributions that delve into theoretical advancements and practical applications of evolutionary optimization. It seeks to provide a comprehensive platform for researchers and practitioners to share insights, methodologies, and breakthrough findings that propel the field forward.
We invite submissions to this Special Issue on topics including, but not limited to:
· Convergence analysis and stability of evolutionary algorithms.
· Novel operators, representations, and hybridization techniques.
· Benchmarking frameworks and performance evaluation.
· Large-scale and high-dimensional optimization.
· Emerging trends in bio-inspired algorithms.
· Advances in multi-objective optimization.
· Adaptive and self-adaptive mechanisms in EAs.
· Machine learning techniques in EAs.
· Engineering design optimization.
· Healthcare and biomedical applications.
· Industrial optimization and automation.
· Evolutionary optimization in big data and AI.
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