Nature-inspired Metaheuristic Algorithms

Solving Real World Engineering Problems

Sulabh Bansal, Aprna Tripathi, Shilpa Srivastava, Prem Prakash Vuppuluri

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040344897
• Topic: Computer Science
• Subtopic: Electrical Engineering & Telecommunications
• Index: Computer Science

This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities.

This book:

• Discusses load balancing and demand response using nature-inspired optimization techniques
• Presents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithms
• Covers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniques
• Explains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniques
• Illustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniques

Nature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Table of contents

• Cover
• Half-Title Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• About the editors
• List of Contributors
• Chapter 1 Introduction to optimization: Techniques and applications in engineering
• Chapter 2 Quantum-inspired evolutionary algorithms: Bridging quantum computing concepts with evolutionary optimization
• Chapter 3 Harnessing metaheuristic algorithms for advanced optimization and design solutions in complex real-world applications
• Chapter 4 A GA-based virtual machine migration technique to optimize data privacy and integrity
• Chapter 5 Hyperparameter tuning of convolutional neural networks using nature-inspired metaheuristic algorithms for image classification
• Chapter 6 Applications of nature-inspired metaheuristic algorithms for medical image analysis
• Chapter 7 Particle swarm optimization for protein structure prediction and refinement
• Chapter 8 Quantum computing-based metaheuristics for medical image segmentation
• Chapter 9 Hybrid metaheuristic approach for community detection
• Chapter 10 Exploring additive manufacturing parameters for improved tensile strength and functional electrode fabrication: A soft computing approach
• Chapter 11 Real-coded genetic algorithm for optimal ordering and pricing in segmented market with freshness and price-dependent demand, advance payment, and trade credit
• Chapter 12 An intelligent simulated annealing model for restraining driver speed on highways with law enforcement in real time
• Chapter 13 Balancing optimization and emissions in heuristics and metaheuristics for hard combinatorial problems
• Chapter 14 Particle swarm optimization-based support vector regression for predictions: Approach and applications
• Chapter 15 Optimizing financial fraud detection models using genetic algorithms
• Index