Course abstract
Evolutionary computation (EC) is a sub-field of computational intelligence that use ideas and get inspiration from natural evolution. It is based on Darwins principle of evolution where the population of individuals iteratively performs search and optimization. EC techniques can be applied to optimization, learning, design and many more. This course will concentrate on the concepts, algorithms, hand-calculations, graphical examples, and applications of EC techniques. Topics will be covered include binary and real-coded genetic algorithms, differential evolution, particle swarm optimization, multi-objective optimization and evolutionary algorithms, and statistical assessment.
Course Instructor
Prof. Deepak Sharma
Deepak Sharma is an Associate Professor in the Department of Mechanical Engineering, Indian Institute of Technology (IIT) Guwahati, India. He obtained his Ph.D. and M.Tech. degrees from IIT Kanpur, India. Prior to joining IIT Guwahati, he has worked with many international research teams at Helsinki School of Economics, Finland; Univesite? de Strasbourg, France; National University of Singapore, Singapore, Karlsruhe Institute of Technology, Germany, and Asian Institute of Technology, Bangkok, Thailand. His research interests include Optimization and Soft Computing Techniques for Design and Optimization, Evolutionary Multi-Objective Optimization, and GPU Computing.More info
Teaching Assistant(s)
No teaching assistant data available for this course yetCourse Duration : Jan-Mar 2022
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Enrollment : 14-Nov-2021 to 31-Jan-2022
Exam registration : 13-Dec-2021 to 18-Feb-2022
Exam Date : 27-Mar-2022
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