Advanced Concepts in Grey Wolf Optimizer - Leading the Pack in Advanced Optimization

Advanced Concepts in Grey Wolf Optimizer: Leading the Pack in Advanced Optimization provides in-depth coverage of recent theoretical advancements in GWO, as well as advanced methods to handle issues such as multiple objectives, constraints, binary variables, large search spaces, dynamic goals, and uncertain data. This book assumes familiarity with optimization fundamentals and therefore dives directly into multi-objective, constrained, binary and dynamic-environment variants, as well as GWO-ML/LLM hybrids. Extensive real-world case studies in areas such as energy systems, supply-chain design, LLM fine-tuning, robotics, and finance ensure that both scholars and engineers can translate the material into deployable solutions. The authors present important new theories, hybrids with Machine Learning/Deep Learning, and hybrid methods that increase GWO's performance. The use of generative AI to improve this algorithm and make it more generic is also explored, along with diverse applications across multiple fields to illustrate the practical utility and versatility of the methods presented. Written by some of the world's most highly cited researchers in the field of artificial intelligence, algorithms, and machine learning, the book serves as an advanced resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.

List of contents

Part 1. Advanced Theory and Methodology
1. Optimizing for the Future: Grey Wolf Algorithm Applications in Emerging Fields
2. GWO and MOGWO in Engineering Optimization: Case Studies and Practical Insights
3. Multi-Objective Parameter Optimisation of External Gear Pumps for Industrial Applications: The GWO Advantage
4. Integrating Fuzzy Logic with Grey Wolf Optimizer for Reinforced Cement Concrete (RCC) Design Optimization
5. Optimizing Crop Selection through Soil Data Analysis using Grey Wolf Optimizer (GWO) with a Multi-objective Clustering Algorithm (MCA)
6. The Role of Grey Wolf Optimizer in Solving Multi-Objective Problems
7. Grey Wolf Optimizer-Based Adaptive Neuro-Fuzzy Inference System for Estimating the Shear Strength of Reinforced Concrete Shear Walls

Part 2. Scalable and High-Performance Computing
8. Advances in Grey Wolf Optimizer: Variants and Applications
9. Navigating the Future: Advancements and Emerging Trends in Grey Wolf Optimization (GWO)
10. Grey Wolf Optimized Xception Model for Enhanced Deepfake Detection
11. Integration of Grey Wolf Optimization and Its Variants with Machine Learning
12. Grey Wolf Optimizer for Hyperparameter Tuning in Machine Learning and AI Techniques: A Nature-Inspired Approach
13. Hybrid Fitness Grey Wolf Optimizer (Fitness GWO) and Sine-Cosine Algorithm with Its Applications in Machine Learning

Part 3. Hybridization with Next-Gen AI Paradigms
14. Large Language Models and Multi-Objective Grey Wolf Optimizer
15. Large Language Model-Based Grey Wolf Optimiser for Supply Chain
16. Gray Wolf Optimizer Combined with Large Language Models for Design Optimization of a Photonic Crystal Filter
17. Optimizing Transformer Model Performance through GWO (Grey Wolf Optimizer)-Based Hyperparameter Tuning
18. Advancing and Investigating Optimization in Graph Neural Networks: Comparative Understandings on GWO-GNN and CDDO-GNN

Part 4. Engineering, Energy, and Infrastructure
19. Current Developments in Multi-Objective Grey Wolf Optimization: A Review of Algorithms and Applications, Modifications, Challenges, and Future Directions
20. Energy Minimisation Strategy of Industrial Methanol Reactor Using Non-Dominated Sorting Grey Wolf Optimizer Algorithm
21. Multi-Objective Grey Wolf Optimizer for Optimal Allocation and Sizing of Energy Storage Systems in Distribution Networks
22. Grey Wolf Optimizer for Civil Engineering: Practical Implementations, Lessons Learned, and Future Directions
23. Optimizing Satellite Attitude Control Controller Gains: A Multi-Objective Approach Using Grey Wolf Optimization
24. Developed Multi-Objective Grey Wolf Optimizer for Optimal Design of Standalone PV Systems
25. Prediction of Compressive Strength of Geopolymer Concrete Using GWO-ANN Hybrid Model
26. Multi-Strategy-Based Grey Wolf Optimization for Spacecraft Design Problems
27. Forecasting Solar Radiation Using a Hybrid Grey Wolf and Water Whale Plant Optimizer
28. Gray Wolf Optimizer: A New-Generation Tool for Studying Solution Existence in Modern Engineering Problems
29. Damage Detection of Truss Structures Using Grey Wolf Optimizer: A State-of-the-Art Review

Part 5. Digital Systems and Cybersecurity
30. Blockchain Scaling Problems Based on Grey Wolf Optimization
31. A Real-World Integrated Process Planning and Scheduling Problem Solved with an Adapted Multi-Objective Grey Wolf Optimizer
32. Hybrid GWO-Based Optimization for Efficient Task Scheduling in IoT-Fog Environments
33. An Efficient Clustering-Based Task Scheduling Using K-Means Grey Wolf Optimizer in IoT Integrated Edge-Cloud Framework
34. Enhancing IoT Intrusion Detection Systems with Grey Wolf Optimizer and Machine Learning
35. Intrusion Detection in Drone Networks Based on Grey Wolf Optimizer and Artificial Neural Networks (GWO-ANN)
36. Grey Wolf Optimizer for Hyperparameter Tuning of Deep Neural Networks for Network Intrusion Detection Systems
37. An Ensemble Method Based on Grey Wolf Optimizer for Hyperparameter Optimization in Missing Data Management in the IoMT
38. Grey Wolf Optimization in Robotics: Cutting-Edge Innovations and Future Opportunities
39. Hybrid CNN and Gray Wolf Optimizer for American Sign Language Classification

Part 6. Life Sciences, Health, and Bioinformatics
40. Intelligent Diagnosis of Liver Disorder with Neuro-Fuzzy Grey Wolf Optimization: A Hybrid Approach
41. CNN Hyperparameter Optimization for COVID-19 Detection in Chest X-Ray Images Using Improved Grey Wolf Optimizer
42. Advancing Population Initialization in Grey Wolf Optimization: A Study on Improving Neural Network Performance for Medical Predictions
43. Gray Wolf Optimization Algorithm in Bioinformatics
44. Hybrid Grey Wolf Optimizer Techniques for Optimal Feature Selection in High-Dimensional Biomedical Data
45. Grey Wolf Optimizer-Based Convolutional Neural Network Model for Diagnosis of Retinal Detachment Diseases through Retinal Fundus Images
46. Quantum-Behaved Grey Wolf Optimization for Precise Segmentation of Kidney Stone CT Images

Part 7. Climate, Environment, and Emerging Paradigms
47. Optimizing Artificial Neural Networks with Grey Wolf Optimizer to Improve Imputation Accuracy of Daily Rainfall Data
48. Integrating Grey Wolf Optimizer with AI and ML Models for Accurate Wind Speed Prediction
49. Enhancing Grey Wolf Optimization Using Reinforcement Learning

About the author

Dr. Seyedali Mirjalili is a Professor and globally renowned leader in artificial intelligence and
optimization, 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 and
Optimization 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 research
publications, 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 The
Australian for five years, his insights have earned significant media attention, which showcases
his influence as a global thought leader.

Product details

• Assisted by: Seyedali Mirjalili (Editor)
• Publisher: Elsevier
• Languages: English
• Product format: Paperback / Softback
• Release: 01.08.2026
• EAN: 9780443457265
• ISBN: 978-0-443-45726-5
• Weight: 450 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; machine learning, Artificial Intelligence, COMPUTERS / Programming / Algorithms, algorithms and data structures, Artificial Intelligence (AI), Algorithms & data structures, Computational Linguistics, COMPUTERS / Artificial Intelligence / General, Natural language and machine translation