Course Content/ Syllabus
Concepts from geometry, calculus, and set theory required in optimization; Unconstrained
Optimization: Conditions for local minimizers, gradient methods, Newton’s method, Least
squares; Duality theory; Constrained Optimization: Lagrange multipliers, KKT
condition; Convex optimization problems; Semi-definite programming; Applications to various
fields of engineering; Numerical software for optimization; Introduction to advanced topics in
Texts: (Format: Authors, Book Title in Italics font, Volume/Series, Edition Number, Publisher,
1. E. K. P. Chong and S. H. Zak, An Introduction to Optimization, 4th Edition., Wiley India Pvt. Ltd., 2013.
2. S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge: Cambridge University Press, 2004.
References: (Format: Authors, Book Title in Italics font, Volume/Series, Edition Number,
1. D. G. Luenberger and Y. Ye, Linear and Nonlinear Programming, 5th Edition., Springer, 2021.