Advances in Metaheuristic Optimization Algorithms
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 821
Special Issue Editor
Special Issue Information
Dear Colleagues,
Metaheuristic optimization algorithms have seen significant advancements in recent decades, driven by their ability to tackle complex and diverse optimization problems across various domains. These algorithms, inspired by natural and artificial processes, have provided robust and flexible solutions for intricate computational challenges. Therefore, this Special Issue aims to highlight the latest developments, innovative methodologies, and practical applications of these algorithms.
We seek papers that explore novel metaheuristic approaches, hybrid algorithms, and their theoretical foundations. Contributions that demonstrate the application of metaheuristic optimization in real-world problems, including but not limited to engineering design, logistics, bioinformatics, finance, and artificial intelligence, are highly encouraged. Additionally, we welcome studies that compare the performance of different metaheuristic techniques, investigate parameter tuning strategies, and propose new benchmarks for algorithm evaluation.
This Special Issue aims to serve as a comprehensive resource for researchers and practitioners, fostering a deeper understanding of metaheuristic optimization and its potential to solve complex problems in various scientific and industrial fields.
Prof. Alma Rodríguez
Guest Editor
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Keywords
- metaheuristics
- swarm intelligence
- evolutionary computation
- artificial intelligence
- bio-inspired optimization methods
- applied optimization
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