Course Name: Traditional And Non-Traditional Optimization Tools

Course abstract

At the beginning of this course, a brief introduction will be given to optimization. The principle of optimization will be explained in detail. The working principles of some traditional tools of optimization, namely exhaustive search method, random walk method, steepest descent method will be discussed with suitable numerical examples. The drawbacks of traditional tools for optimization will be stated. The working principle of one of the most popular non-traditional tools for optimization, namely genetic algorithm (GA) will be explained in detailed. Schema theorem of binary-coded GA will be discussed. The methods of constraints handling used in the GA will be explained. The merits and demerits of the GA will be stated. The working principles of some specialized GAs, such as real-coded GA, micro-GA, visualized interactive GA, scheduling GA will be discussed with suitable examples. The principles of some other non-traditional tools for optimization, such as simulated annealing, particle swarm optimization will be explained in detail. After providing a brief introduction to multi-objective optimization, the working principles of some of its approaches, namely weighted sum approach, goal programming, vector-evaluated GA (VEGA), distance- based Pareto-GA (DPGA), non-dominated sorting GA (NSGA) will be explained with the help of numerical examples.


Course Instructor

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Prof. Dilip Kumar Pratihar

I received BE (Hons.) and M. Tech. from REC (NIT) Durgapur, India, in 1988 and 1994, respectively. I obtained my Ph.D. from IIT Kanpur, India, in 2000. I received University Gold Medal, A.M. Das Memorial Medal, Institution of Engineers’ (I) Medal, and others. I completed my post-doctoral studies in Japan and then, in Germany under the Alexander von Humboldt Fellowship Programme. I received Shastri Fellowship (Indo-Canadian) in 2019 and INSA Teachers’ Award 2020. I am working now as a Professor (HAG scale) of IIT Kharagpur, India. My research areas include robotics, soft computing and manufacturing science. I have published more than 275 papers and book-chapters. I have written the textbooks on “Soft Computing” and “Fundamentals of Robotics”, co-authored another textbook on “Analytical Engineering Mechanics”, edited a book on “Intelligent and Autonomous Systems”, co-authored reference books on “Modeling and Analysis of Six- legged Robots” “Modeling and Simulations of Robotic Systems Using Soft Computing” “Modeling and Analysis of Laser Metal Forming Processes by Finite Element and Soft Computing Methods” and “Multibody Dynamic Modeling of Multi-legged Robots”. My textbook on “Soft Computing” had been translated into Chinese language in 2009. I have guided 22 Ph.D.s. I am in editorial board of 10 International Journals. I have been elected as FIE, MASME and SMIEEE. I have completed a few sponsored (funded by DST, DAE, MHRD) and consultancy projects. I have filed two patents.
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 Course 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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Total Enrollment: 301

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