Course Archives Theoretical Statistics and Mathematics Unit

Course: Optimization Instructor: Soumyashant Nayak Room: G23 Level: Undergraduate Time: Currently offered

Syllabus Past Exams Syllabus: Perron-Frobenius theory. LINEAR PROGRAMMING: Basic notions; fundamental theorem of LP; the simplex algorithm; duality and applications. Karmarkars algorithm. CONSTRAINED OPTIMIZATION PROBLEMS: Equality constraints, Lagrange multipliers; Inequality constraints, Karush-Kuhn-Tucker theorem; Illustrations (including situations where the above can fail). FURTHER TOPICS: Convexity and optimization. Unconstrained optimization problems and descent methods Reference Texts: (a) H. Karloff: Linear Programming (b) Sher-Cherng Fang and Sarat Puthenpura: Linear optimization and extensions Theory and algorithms (c) R. K. Sundaram: A first course in optimization Theory (d) S. Boyd and L. Vendenberhe: Convex Optimization (e) S. J. Miller: Mathematics of optimization: how to do things faster (f) D. Bertsimas and J. Tsitsikilis: Introduction to Linear Optimization (g) D. Bertsekas: Convex Optimization Theory Evaluation: Mid-term 30 marks Assignment 20 marks Final Exam 50 marks Total 100 marks Top of the page Past Exams

Midterm 24.pdf Semestral 24.pdf Supplementary and Back Paper Top of the page

[ Semester Schedule ][ Statmath Unit ] [Indian Statistical Institute]