Evolutionary Computation
Techniques and Applications

Editors: Ashish M. Gujarathi, PhD
B. V. Babu, PhD

Evolutionary Computation

Pub Date: November 2016
Hardback Price: $189.95 US
Hard ISBN: 9781771883368
E-Book ISBN: 9781315366388
Pages: 652 pp w/ index
Binding Type: hardback
Notes: 34 color and 172 b/w illustrations

Evolutionary computation has gained popularity in the recent past due to its several advantages over deterministic methods. Unlike deterministic methods, evolutionary computation methods starts with multiple solutions (both for single- and multi-objective optimization [MOO] studies) in order to attain a wide range of initial population members. Evolutionary computation methods are also highly preferred for solving multi-objective optimization problems where conflicting objective functions are involved. This volume presents and discusses recent advancements in evolutionary computation of both theory and applications. Both scientific and engineering applications of evolutionary computation techniques are explored here.

This book is broadly organized into three sections:

  • theory and applications in engineering systems
  • theory and applications of single objective optimization
  • theory and applications of single and multi-objective optimization studies
Edited by professionals with years of experience, Evolutionary Computation: Techniques and Applications provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications.

Covering both the theory and applications of evolutionary computation, the book
  • offers exhaustive coverage of several topics on nontraditional evolutionary techniques
  • covers detailed working principles of new and popular evolutionary algorithms
  • discusses case studies on both scientific and real-world applications of optimization
The book will be valuable for faculty and researchers as well as advanced students in the areas of optimization, evolutionary computation, modeling and simulation, process plant simulation, and more.

Section 1. Theory and Applications in Engineering Systems
1. Introduction
Ashish M. Gujarathi, and B. V. Babu
2. Bio-Mimetic Adaptations of Genetic Algorithm and Their Applications to Chemical Engineering
Vibhu Trivedi and Manojkumar Ramteke
3. Surrogate-Assisted Evolutionary Computing Methods
Saket Kansara, Sumeet Parashar, and Abdus Samad
4. Evolutionary Algorithms in Ironmaking Applications
Tamoghna Mitra, Henrik Saxén, and Nirupam Chakraborti
5. Harmony Search Optimization for Multilevel Thresholding in Digital Images
Diego Oliva, Erik Cuevas, Gonzalo Pajares, Daniel Zaldívar, Marco Pérez-Cisneros, and Valentín Osuna-Enciso
6. Swarm Intelligence in Software Engineering Design Problems
Tarun Kumar Sharma and Millie Pant
7. Gene Expression Programming in Nanotechnology Applications
Pravin M. Singru, Vishal Jain, Nikilesh Krishnakumar, A. Garg, K. Tai, and V. Vijayaraghavan

Section 2. Theory and Applications of Single Objective Optimization Studies
8. An Alternate Hybrid Evolutionary Method for Solving MINLP Problems
Munawar A. Shaik and Ravindra D. Gudi
9. Differential Evolution for Optimal Design of Shell-and-Tube Heat Exchangers
Munawar A. Shaik and B. V. Babu
10. Evolutionary Computation Based QoS-Aware Multicast Routing
Manas Ranjan Kabat, Satya Prakash Sahoo, and Manoj Kumar Patel
11. Performance Assessment of the Canonical Genetic Algorithm: A Study on Parallel Processing Via GPU Architecture
Paulo Fazendeiro and Paula Prata
12. An Efficient Approach for Populating Deep Web Repositories Using SFLA
Hema Banati and Shikha Mehta
13. Closed Loop Simulation of Quadraple Tank Process Using Adaptive Multi-Loop Fractional Order PID Controller Optimized Using Bat Algorithm
U. Sabura Banu

Section 3. Theory and Applications of Single and Multi-Objective Optimization Studies
14. A Practical Approach towards Multi Objective Shape Optimization
G. N. Sashi Kumar
15. Nature-Inspired Computing Techniques for Integer Factorization
Mohit Mishra, S. K. Pal, and R. V. Yampolskiy
16. Genetic Algorithm Based Real-Time Parameter Identifier for an Adaptive Power System Stabilizer
Wael Mohamed Fayek and O. P. Malik
17. Applied Evolutionary Computation in Fire Safety Upgrading
Iordanis A. Naziris, Nikos D. Lagaros, and Kyriakos Papaioannou
18. Elitist Multi-Objective Evolutionary Algorithms for Voltage and Reactive Power Optimization in Power Systems
S. B. Dharam Veer P. S. Anauth and Robert T. F. Ah King
19. Evaluation of Simulated Annealing, Differential Evolution and Particle Swarm Optimization for Solving Pooling Problems
Ying Chuan Ong, Shivom Sharma, and G. P. Rangaiah
20. Performance Improvement of NSGA-II Algorithm by Modifying Crossover Probability Distribution
K .V. R. B. Prasad and P. M. Singru
21. Evolutionary Algorithms for Malware Detection and Classification
Kamran Morovati and Sanjay S. Kadam

About the Authors / Editors:
Editors: Ashish M. Gujarathi, PhD
Assistant Professor, Petroleum and Chemical Engineering Department, College of Engineering, Sultan Qaboos University, Sultanate of Oman

Ashish M. Gujarathi, PhD, is currently an Assistant Professor in the Petroleum and Chemical Engineering Department of the College of Engineering at Sultan Qaboos University, Sultanate of Oman. He was formerly a Lecturer of Chemical Engineering at the Birla Institute of Technology and Science (BITS) in Pilani, India. Dr. Gujarathi has over eleven years of experience as a chemical engineer with diverse work experience comprising a blend of academic research, teaching, and industrial consultancy work. A prolific author with articles, book chapters, and conference proceedings to his credit, he is also an editorial board member of several journals, including the Journal of Developmental Biology and Tissue Engineering and the International Open Access Journal of Biology and Computer Science and has acted as a reviewer for several international journals as well as for books and conference proceedings. His research interests include reaction engineering; process design and synthesis; process modeling, simulation, and optimization; polymer science and engineering; petrochemicals; parametric estimation and optimization of major chemical processes; evolutionary computation; and biochemical engineering.

B. V. Babu, PhD
Vice Chancellor, Galgotias University, Greater Noida, India

B. V. Babu, PhD, is currently Vice Chancellor at Galgotias University in Greater Noida, India. An acknowledged researcher and renowned academician, Dr. Babu has 30 years of teaching, research, consultancy, and administrative experience. Formerly, he was the Pro Vice Chancellor of DIT University, Dehradun and founding Director of the Institute of Engineering and Technology (IET) at JK Lakshmipat University, Jaipur. He is a member of many national and international academic and administrative committees and professional organizations. Professor Babu is a distinguished academician and an acknowledged researcher and is well-known internationally for his algorithm MODE (Multi Objective Differential Evolution) and its improved variants. Overall he has over 235 research publications to his credit. He has published several books and has written chapters, invited editorials, and articles in various books, lecture notes, and international journals. He organized several international and national conferences, workshops, and seminars and also chaired several technical sessions. He has been invited speaker and has delivered keynote addresses at various international conferences, seminars, and workshops. He is the recipient of CSIR’s National Technology Day Award for recognition his research work as well as of many other awards. He is the life member/fellow of many professional bodies such as IIChE, IE (I), ISTE, ICCE, IEA, SOM, ISSMO, IIIS, IAENG, SPE, ISTD, etc. He is editor-in-chief and editorial board member of several international and national scientific journals.

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