Metaheuristic Optimization for Social Good

Dr. Thompson Stephan serves as an Assistant Professor at Thumbay College of Management and AI in Healthcare, Gulf Medical University, Ajman, United Arab Emirates. Dr. Thompson Stephan earned his PhD from Pondicherry University, India, in 2018, complemented by full-time research and industry expertise. Dr. Stephan has received prestigious accolades, including the Best Researcher Award in 2020 and the Protsahan Research Award in 2023, both from the IEEE Bangalore Section, India. His primary research focus is in artificial intelligence, with specialized expertise in advancing machine learning, data mining, and metaheuristic optimization, particularly in the context of high-dimensional data. With more than 80 Scopus-indexed publications, including 47 in SCI-indexed journals, Thompson’s work has garnered significant recognition. He actively contributes as a book editor and reviewer for esteemed international journals, with publications on leading platforms such as IEEE, Elsevier, Taylor & Francis, and Springer. Dr. Stephan has successfully four Scopus indexed edited book, two with Springer and two with Taylor & Francis, with another ongoing Springer book titled Hybrid Metaheuristic Optimization for Engineering Applications. Dr. Seyedali Mirjalili is a Professor and globally renowned leader in artificial intelligence andoptimization, recognized as the No. 1 AI researcher on Stanford University’s prestigious World’s Top Scientists list since 2023. He founded the Centre for Artificial Intelligence Research andOptimization in 2019 and serves as a Professor of AI at Torrens University Australia, with distinguished professorships in Hungary and the Czech Republic. With more than 600 researchpublications, 130,000 citations, and an H-index of 125, Prof. Mirjalili is among the top 1% of highly cited researchers worldwide. His contributions include developing AI algorithms widely applied in science and industry and delivering influential talks, including a TED Talk on AI's transformative potential. Prof. Mirjalili is a strong advocate for responsible and inclusive AI, and he has collaborated with industry and government on ethical AI tools. As a senior member of IEEE and an editor for leading AI journals, he significantly contributed to the advancements of fundamental and applied research in the field. Recognized as a top research leader by TheAustralian for five years, his insights have earned significant media attention, which showcaseshis influence as a global thought leader. Dr. Vinaytosh Mishra is an Associate Professor and Associate Dean at the Thumbay College of Management and AI in Healthcare, Gulf Medical University, UAE. He holds a PhD in Healthcare Supply Chain Management and has completed postdoctoral fellowships in AI in Healthcare and Ethical AI. With more than 19 years of experience spanning information technology, manufacturing, finance, healthcare, and education, he has held leadership roles including CEO of a multispecialty hospital. His research and teaching focuses on supply chain management, operations management, business analytics, AI-enabled decision support, digital transformation, optimization, simulation, Lean Six Sigma, and digital twins. He is an inventor on one Australian and two German patents in AI for healthcare and serves as a domain expert for AI implementation in healthcare at AHB.ai in Sharjah, UAE. He has designed and launched successful undergraduate and postgraduate programs in healthcare management and AI in healthcare.

• 1. Metaheuristic Algorithms for Societal Impact. An Overview2. EQUI-MetaOpt. An Ethical Metaheuristic Framework for Equitable AI Optimization3. Green-Energy MHO. A Metaheuristic Optimization Technique for Sustainable Power Distribution4. Application of Grey Wolf Optimizer Algorithm for Load Frequency Control in Interconnected Power Systems5. A Novel Metaheuristic Planner for Sustainable Traffic and Infrastructure6. MediSchedA Metaheuristic Approach to Optimal Hospital Resource Scheduling7. A Metaheuristic Technique for Fair Education Resource Allocation8. A Data-Driven Metaheuristic Framework for Community Health Resource Optimization9. Hybrid Metaheuristics for Potato Price Prediction with Time Series10. Metaheuristic-Optimized Feature Selection and Machine Learning for Scalable Bearing Fault Diagnosis Across Diverse Operating Conditions11. Hybrid-SPO/GWO-KNN. A Hybrid Binary Stochastic Paint Optimizer and Grey Wolf Optimizer with K-Nearest Neighbor Classifier for Feature Selection12. Improved-GWO. An Improved Grey Wolf Optimizer for Wrapper Feature Selection13. Sync-Async-GWO. Group-Based Synchronous-Asynchronous Grey Wolf Optimizer Enhanced by Diversity and Stagnation Control14. Hybrid-B-GWO-SFS. Feature Selection Based on Hybrid Binary Grey Wolf Optimizer and Stochastic Fractal Search Algorithm15. PSO-vs-ABC. Comparative Analysis of Particle Swarm Optimization and Artificial Bee Colony Algorithms for Non-Rigid Medical Image Registration16. Meta-Heuristics + LLMs. Combined Metaheuristics with Large Language Models for Photonic Filter Design17. MFDO-GWO. Advanced Hybrid Approach of Modified Falcon Optimization and Grey Wolf Optimization for Robust Engineering Applications18. GWO-MGO. A Novel Hybrid Grey Wolf Optimizer with Mountain Gazelle Optimizer Algorithms for Solving Uncapacitated Facility Location Problems19. Applying Metaheuristics for Risk-Aware Portfolio Optimization20. Future Trends in Metaheuristic Optimization for Social Good