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Metaheuristic-Driven Optimization Algorithms: Methods and Applications

Submission Deadline: 31 December 2024 Submit to Special Issue

Guest Editors

Prof. Mohammad Shokouhifar, Shahid Beheshti University, Iran
Prof. Frank Werner, Otto-Von-Guericke-University, Germany

Summary

The exploration of optimization problems spans numerous scientific and engineering domains, sparking a growing need for refined optimization techniques. While exact search methods consistently yield the optimal solution, their feasibility diminishes when tackling real-world NP-complete/hard problems due to time constraints. This emphasizes the significance of metaheuristic algorithms that offer near-optimal solutions within a reasonable timeframe while maintaining a beneficial balance between complexity and efficiency. One primary advantage of metaheuristics is their adaptability as general-purpose, problem-independent algorithms. Unlike exact algorithms, metaheuristics depend less on mathematical models and thrive on the "trial-and-error" principle in searching for optimal solutions, excelling in evading local optima across various problems.


This Special Issue invites academia and industry experts to showcase the latest advancements in metaheuristic algorithms and their practical applications in solving real-world optimization problems across various engineering fields including computer, electrical, mechanical, chemical, biomedical, civil, and industrial engineering. Potential topics include, but are not restricted to:

  • Development of new single-solution metaheuristic algorithms

  • Advancements in population-based metaheuristic algorithms

  • Evolution of multi-objective metaheuristic algorithms

  • Ensemble knowledge-based heuristic-metaheuristic algorithms

  • Fusion of fuzzy systems and metaheuristics for optimization

  • Hybridization of machine learning and metaheuristics for optimization

  • Metaheuristic-driven heuristics tailored for Just-in-Time (JIT) optimization

  • Applications in signal, image, and video processing   

  • Applications in healthcare big data analytics

  • Applications in scheduling and resource allocation problems  

  • Applications in optimal design of renewable energy systems

  • Applications in smart manufacturing and supply chain logistics

  • Applications in business intelligence and financial management

  • Applications in Internet-of-Things (IoT) and smart cities

  • Applications in computer and communication networks


Keywords

Optimization, Engineering Problems, Metaheuristics, Evolutionary Algorithms, Swarm Intelligence, Multi-Objective Optimization, Ensemble Metaheuristic Algorithms

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