Course Archives Theoretical Statistics and Mathematics Unit
Course: Optimization
Instructor: Mathew Joseph
Room: G23
Level: Undergraduate
Time: Currently offered
Past Exams


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

Mid-term 30 marks
Assignment 20 marks
Final Exam 50 marks
Total 100 marks

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Past Exams
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