Evolutionary Computation (eBook, ePUB)

Techniques and Applications
Redaktion: Gujarathi, Ashish M.; Babu, B. V.

• Format: ePub

Produktbeschreibung

Edited by professionals with years of experience, this book 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, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 652
• Erscheinungstermin: 1. Dezember 2016
• Englisch
• ISBN-13: 9781315342160
• Artikelnr.: 47902781

Autorenporträt

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, 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.

Inhaltsangabe

Theory and Applications in Engineering Systems. Introduction. Bio-Mimetic
Adaptations of Genetic Algorithm and Their Applications to Chemical
Engineering. Surrogate-Assisted Evolutionary Computing Methods.
Evolutionary Algorithms in Ironmaking Applications. Harmony Search
Optimization for Multilevel Thresholding in Digital Images. Swarm
Intelligence in Software Engineering Design Problems. Gene Expression
Programming in Nanotechnology Applications. Theory and Applications of
Single Objective Optimization Studies. An Alternate Hybrid Evolutionary
Method for Solving MINLP Problems. Differential Evolution for Optimal
Design of Shell-and-Tube Heat Exchangers. Evolutionary Computation Based
QoS-Aware Multicast Routing. Performance Assessment of the Canonical
Genetic. An Efficient Approach for Populating Deep Web Repositories Using
SFLA. Closed Loop Simulation of Quadraple Tank Process Using Adaptive
Multi-Loop Fractional. Theory and Applications of Single and
Multi-Objective Optimization Studies. A Practical Approach towards Multi
Objective Shape Optimization. Nature-Inspired Computing Techniques for
Integer Factorization. Genetic Algorithm Based Real-Time Parameter
Identifier for an Adaptive Power System Stabilizer. Applied Evolutionary
Computation in Fire Safety Upgrading. Elitist Multi-Objective Evolutionary
Algorithms for Voltage and Reactive Power Optimization in Power Systems.
Evaluation of Simulated Annealing, Differential Evolution and Particle
Swarm Optimization for Solving Pooling Problems. Performance Improvement of
NSGA-II Algorithm by Modifying Crossover Probability Distribution.
Evolutionary Algorithms for Malware Detection and Classification. Index.