Optimization Theory (IE 601)

2021 Spring
Faculty of Engineering and Natural Sciences
Industrial Engineering(IE)
3
10.00
Burak Kocuk burakkocuk@sabanciuniv.edu,
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English
Doctoral, Master
IE501
Formal lecture
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CONTENT

Convex optimization and functional analysis; theory of duality; iterative methods and convergence proofs; interior point methods for linear programming; computational complexity of mathematical programming problems; extensions of linear programming.

OBJECTIVE

Refer to the course content

LEARNING OUTCOME

Understand the relationship between linear programming, convex programing and conic programming
Understand the theoretical foundation of conic programming
Learn applications of conic programming in engineering optimization and nonconvex optimization
Learn interior point methods and computational complexity of linear programming

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 30
Midterm 20
Individual Project 20
Homework 30

RECOMENDED or REQUIRED READINGS

Readings

Lectures on Modern Convex Optimization, A. Ben-Tal and A. Nemirovski (SIAM).
Convex Optimization, S. Boyd and L. Vandenberghe (Cambridge University Press).
Numerical Optimization, J. Nocedal and S. Wright (Springer Press).