Optimizing Engineering Problems Through Heuristic Techniques

1. Auflage 2019
ISBN: 978-1-138-48536-5
Verlag: CRC PR INC

Buch, Englisch, 152 Seiten, Format (B × H): 155 mm x 239 mm, Gewicht: 340 g

Reihe: Science, Technology, and Management

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

Autoren/Hrsg.

Kumar, Kaushik

Zindani, Divya

Davim, J. Paulo

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz
• Technische Wissenschaften Technik Allgemein Industrial Engineering
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

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.

Über Autor(innen)

Kaushik Kumar, B.Tech (Mechanical Engineering, REC (Now NIT), Warangal), MBA (Marketing, IGNOU) and Ph.D (Engineering, Jadavpur University), is presently an Associate Professor in the Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, India. He has 18 years of Teaching & Research and over 11 years of industrial experience in a manufacturing unit of Global repute. His areas of teaching and research interest are Conventional and Non-conventional Quality Management Systems, Optimization, Non-conventional machining, CAD / CAM, Rapid Prototyping and Composites. He has 9 Patents, 28 books, 19 Edited Book Volume, 43 Book Chapters, 141 international Journal, 21 International and 8 National Conference publications to his credit. He is Editor–in–Chief, Series Editor, Guest Editor, Editor, Editorial Board member and Reviewer for International and National Journals. He has been felicitated with many awards and honours.

Divya Zindani, (BE, Mechanical Engineering, Rajasthan Technical University, Kota), M.E. (Design of Mechanical Equipment, BIT Mesra), presently pursuing PhD (National Institute of Technology, Silchar). He has over 2 years of Industrial experience. His areas of interests are Optimization, Product and Process Design, CAD/CAM/CAE, Rapid prototyping and Material Selection. He has 1 Patent, 4 Books, 6 Edited Books, 18 Book Chapters, 2 SCI journal, 7 Scopus Indexed international journal and 4 International Conference publications to his credit.

J. Paulo Davim received his Ph.D. degree in Mechanical Engineering in 1997, M.Sc. degree in Mechanical Engineering (materials and manufacturing processes) in 1991, Mechanical Engineering degree (5 years) in 1986, from the University of Porto (FEUP), the Aggregate title (Full Habilitation) from the University of Coimbra in 2005 and the D.Sc. from London Metropolitan University in 2013. He is Senior Chartered Engineer by the Portuguese Institution of Engineers with an MBA and Specialist title in Engineering and Industrial Management. He is also Eur Ing by FEANI-Brussels and Fellow (FIET) by IET-London. Currently, he is Professor at the Department of Mechanical Engineering of the University of Aveiro, Portugal. He has more than 30 years of teaching and research experience in Manufacturing, Materials, Mechanical and Industrial Engineering, with special emphasis in Machining & Tribology. He has also interest in Management, Engineering Education and Higher Education for Sustainability. He has guided large numbers of postdoc, Ph.D. and master’s students as well as has coordinated and participated in several financed research projects. He has received several scientific awards. He has worked as evaluator of projects for ERCEuropean Research Council and other international research agencies as well as examiner of Ph.D. thesis for many universities in different countries. He is the Editor in Chief of several international journals, Guest Editor of journals, books Editor, book Series Editor and Scientific Advisory for many international journals and conferences. Presently, he is an Editorial Board member of 30 international journals and acts as reviewer for more than 100 prestigious Web of Science journals. In addition, he has also published as editor (and co-editor) more than 100 books and as author (and co-author) more than 10 books, 80 book chapters and 400 articles in journals and conferences (more than 250 articles in journals indexed in Web of Science core collection/h-index 50+/7500+ citations, SCOPUS/h-index 56+/10500+ citations, Google Scholar/h-index 71+/16500+).