Nature-inspired Metaheuristic Algorithms
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Nature-inspired Metaheuristic Algorithms: Solving Real World Engineering Problems

Nature-inspired Metaheuristic Algorithms: Solving Real World Engineering Problems

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About the Book

The text comprehensively provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It will further demonstrate 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. The text 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:
1. Introduction to Optimization: Techniques and Application in Engineering. 2. Quantum-Inspired Evolutionary Algorithms: Bridging Quantum Computing Concepts with Evolutionary Optimization. 3. Harnessing Metaheuristic Algorithms for Advanced Optimization and Design Solutions in Complex Real-World Applications. 4. A GA-Based Virtual Machine Migration Technique to Optimize Data Privacy and Integrity. 5. Hyperparameter Tuning of Convolutional Neural Networks using Nature-Inspired Metaheuristic Algorithms for Image Classification. 6. Applications of Nature-Inspired Metaheuristics Algorithms for Medical Image Analysis. 7. Particle Swarm Optimization for Protein Structure Prediction and Refinement. 8. Quantum Computing Based Metaheuristics for Medical Image Segmentation. 9. Hybrid Meta-heuristic Approach for Community Detection. 10. Exploring Additive Manufacturing Parameters for Improved Tensile Strength and Functional Electrode Fabrication: A Soft Computing Approach. 11. Application of Real Coded Genetic Algorithm for Optimal Ordering, Pricing and Discounting Policies in the presence of Partial Advance Payment and Trade Credit in a Segmented Market with Freshness and Price Dependent Demand. 12. An Intelligent Simulated Annealing Model for Restraining Driver Speed on Highways with Law Enforcement in Real-Time. 13. Balancing Optimization and Emissions in Heuristics and Metaheuristics for Hard Combinatorial Problems. 14. Particle Swarm ptimization-Based Support Vector Regression for Predictions: Approach and Applications. 15. Optimizing Financial Fraud Detection Models Using Genetic Algorithms.


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Product Details
  • ISBN-13: 9781040344873
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Language: English
  • ISBN-10: 1040344879
  • Publisher Date: 10 Jun 2025
  • Binding: Digital (delivered electronically)
  • Sub Title: Solving Real World Engineering Problems


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Nature-inspired Metaheuristic Algorithms: Solving Real World Engineering Problems
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Nature-inspired Metaheuristic Algorithms: Solving Real World Engineering Problems
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