Grey Wolf Optimizer

A Pack of Solutions for Your Optimization Problems

Seyedali Mirjalili

• Publisher: Morgan Kaufmann
• Year: 2026
• Topic: Computer Science
• eBook ISBN:
  9780443366253
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Grey Wolf Optimizer: A Pack of Solutions for Your Optimization Problems offers in-depth coverage of recent theoretical advancements in GWO, as well as several variants, improvements, and hybrid approaches developed to enhance the GWO's performance and adaptability. 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. The book offers a deep dive into the algorithm's foundations and presents new developments to help researchers overcome common challenges.It features numerous case studies and real-world examples across various fields, such as engineering, healthcare, finance, and environmental management. These applications demonstrate the versatility and effectiveness of the GWO in addressing complex, interdisciplinary challenges, making the content highly relevant and practical for readers. 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 essential resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer. - Helps readers understand the evolution, strengths, and current standing of the Grey Wolf Optimizer as a powerful optimization technique - Helps readers grasp the core concepts and theoretical foundations necessary for effective application - Introduces novel variants, improvements, and hybrid approaches designed to tackle optimization problems involving binary, multi-objective, noisy, dynamic, and combinatorial challenges - Features numerous case studies and real-world examples across various fields, such as engineering, healthcare, finance, and environmental management

Table of contents

• Title of Book
• Chapter 1 Grey wolf optimizer: mathematical principles, computational complexity, convergence proof, and performance analysis
• Chapter 2 A multipopulation grey wolf optimizer with adaptive size reduction and solution exchange for multilevel thresholding in image segmentation
• Chapter 3 Theoretical foundations and methodologies of the grey wolf optimizer
• Chapter 4 In-depth mathematical analysis, dynamic behavior, and convergence proof of the grey wolf pptimizer
• Chapter 5 Binary grey wolf and football optimization algorithm for potato leaf disease image classification with deep learning
• Chapter 6 Bibliometric analysis of the grey wolf optimizer
• Chapter 7 An enhanced medical prediction model for diabetes using grey wolf optimizer-assisted wrapper-based algorithms
• Chapter 8 Performance analysis of the grey wolf optimizer and its variants in global search optimization
• Chapter 9 Optimal parameter prediction for photovoltaic modules using the grey wolf optimizer: a case study from a university-based photovoltaic station in Türkiye
• Chapter 10 Predictive bridge deterioration modeling with a hybrid stochastic paint optimizer, grey wolf optimizer, and extreme learning machine algorithm
• Chapter 11 Performance comparison of grey wolf optimizer-tuned controllers in functional electrical stimulation applications
• Chapter 12 Grey wolf optimizer algorithm for buckling load maximization of stiffened piezolaminated composite plates
• Chapter 13 Efficient application mapping onto three-dimensional network-on-chips using the grey wolf optimizer
• Chapter 14 Line sampling method based on grey wolf optimizer for structural reliability analysis
• Chapter 15 Applications and real-world case studies: the grey wolf optimizer for feature selection in intrusion detection systems
• Chapter 16 Optimizing solutions of fractional differential equations using the grey wolf optimizer and homotopy analysis method
• Chapter 17 Performance evaluation of the grey wolf optimizer against advanced differential evolution variants
• Chapter 18 Grey wolf optimizer enabled optimization of Ti6Al4V surface morphology and wear behavior
• Chapter 19 Budget constrained fairness aware incentive recommendation with uplift modeling using grey wolf optimization
• Chapter 20 Applications of grey wolf optimizer and its variants in wireless sensor networks
• Chapter 21 Comparative performance analysis of binary grey wolf optimizer and teaching-learning-based algorithm for the traveling salesman problem
• Chapter 22 A hybrid GWO-PSO algorithm for sliding surface design in sliding mode control of 6R robot manipulators
• Chapter 23 Applications of the grey wolf optimizer in water engineering and management
• Chapter 24 Optimizing enterprise information system security with the grey wolf optimizer: a novel approach to risk assessment and asset prioritization
• Chapter 25 Application of the grey wolf optimizer to enhance offshore microgrid power management and control including tidal power and desalination
• Chapter 26 A hybrid grey wolf optimizer and flying squirrel algorithm for single foundation design
• Chapter 27 A comparative analysis of the grey wolf optimizer and genetic algorithms
• Chapter 28 Enhancing hub-motor performance in electric vehicles: grey wolf multiobjective design optimizer to resolve performance trade-offs
• Chapter 29 Uncertainty and sensitivity evaluation in joint geophysical inversion using a hybrid grey wolf optimizer and particle swarm optimization algorithm
• Chapter 30 Optimized finite impulse response adaptive noise cancellation for improved photoplethysmography signal enhancement using the grey wolf optimizer
• Chapter 31 Multilabel feature selection using grey wolf optimizer and mutual information
• Chapter 32 Comparative analysis of grey wolf optimizer with other metaheuristics algorithms
• Chapter 33 Binary grey wolf optimizer for solving various resolving set problems
• Chapter 34 Enhanced autonomous vehicle navigation using a pure pursuit and grey wolf optimizer algorithm
• Chapter 35 Can the grey wolf optimizer solve daily life problems?
• Chapter 36 RCGWO: an improved grey wolf optimization algorithm using random weight and elite-based crossover for solving real world optimization problems
• Chapter 37 An adaptive hybrid grey wolf optimizer and teaching-learning-based optimization algorithm for team formation optimization problems
• Chapter 38 A concurrent power distribution systems model for demand-supply scheduling using the grey wolf optimizer
• Glossary
• Index