Optimizing Engineering Problems through Heuristic Techniques

✍ Scribed by Kaushik Kumar (Author); Divya Zindani (Author); J. Paulo Davim (Author)

• Publisher: CRC Press
• Year: 2019
• Leaves: 151
• Edition: 1
• Category: Library

✦ Synopsis

This book will cover heuristic optimization techniques and applications in engineering problems. The book will be divided into three sections that will provide coverage of the techniques, which can be employed by engineers, researchers, and manufacturing industries, to improve their productivity with the sole motive of socio-economic development. This will be the first book in the category of heuristic techniques with relevance to engineering problems and achieving optimal solutions.

Features

• Explains the concept of optimization and the relevance of using heuristic techniques for optimal solutions in engineering problems
• Illustrates the various heuristics techniques
• Describes evolutionary heuristic techniques like genetic algorithm and particle swarm optimization
• Contains natural based techniques like ant colony optimization, bee algorithm, firefly optimization, and cuckoo search
• Offers sample problems and their optimization, using various heuristic techniques

✦ Table of Contents

Section 1: Introduction to Optimization and Relevance of Heuristic Techniques Towards Optimal Solution. Chapter 1. Optimization Using Heuristic Search: An Introduction. Section 2: Description of Heuristic Optimization Techniques. Part 1: Evolutionary Techniques. Chapter 2. Genetic Algorithm. Chapter 3. Particle Swarm Optimization Algorithm. Part 2: Nature-Based Techniques. Chapter 4. Ant Colony Optimization. Chapter 5. Bees Algorithm. Chapter 6. Firefly Algorithm. Chapter 7. Cuckoo Search Algorithm. Section 3: Application of Heuristic Techniques Toward Engineering Problems. Chapter 8. Engineering Problem Optimized Using Genetic Algorithm. Chapter 9. Engineering Problem Optimized Using Particle Swarm Optimization Algorithm. Chapter 10. Engineering Problem Optimized Using Ant Colony Optimization Algorithm. Chapter 11. Engineering Problem Optimized Using Bees Algorithm. Chapter 12. Engineering Problem Optimized Using Firefly Optimization Algorithm. Chapter 13. Engineering Problem Optimized Using Cuckoo Search Algorithm. References. Index.