Course Archives Theoretical Statistics and Mathematics Unit

Course: Optimization Instructor: Mathew Joseph 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 Supplementary and Back Paper Top of the page

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