Syllabus (Core): M.Tech

Optimization

Code: EE 557 | L-T-P-C : 3-0-0

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

optimization;

Texts: (Format: Authors, Book Title in Italics font, Volume/Series, Edition Number, Publisher,

Year.)

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,

Publisher, Year.)

1. D. G. Luenberger and Y. Ye, Linear and Nonlinear Programming, 5th Edition., Springer, 2021.