INTRODUCTION TO OPTIMIZATION  (EHB474E)

 

Instructor:

M. Ertuğrul Çelebi,  Professor

Room:  2420

Phone: (212) 285 3558

E-Mail:  mecelebi@itu.edu.tr

Url: https://web.itu.edu.tr/~mecelebi

Office Hours:  Wednesday's after 14:30 by appointment.

 

Course Objective:

To obtain basic concepts of optimization methods with applications to telecommunications

 

Content:

Review of linear algebra and multivariable calculus, unconstrained optimization, gradient and Newton's

methods, equality and inequality constraints, least-squares method, linear programming, simplex method,

issues of network optimization, optimization case studies in signal processing and telecommunications.

 

Grading Policy:

% 35 Midterm,  % 45 Final, %20 Homework.

Homework will be collected at the beginning of the first lecture of the due date. No exceptions.

 

Textbook:

An Introduction to Optimization, 4th Ed., Edwin K.P. Chong, Stanislaw H. Zak, Wiley, 2013

 

Useful Books:

Optimization Concepts and Applications in Engineering,  3rd Ed., Ashok D. Belegundu, 

    Tirupathi R. Chandrupatla, Cambridge Un. Press, 2019

Introduction to Optimization, P. Pedregal, Springer, 2004

Linear and Nonlinear Programming, 3rd Ed., David G. Luenberger, Yinyu Ye, Springer, 2008

Convex Optimization, Stephen Boyd, L. Wandenberghe, Cambridge U. Press, 2004
    Available for download at www.stanford.edu/~boyd/cvxbook/
Nonlinear Programming, Dimitri P. Bertsekas, Athena Scientific, 1999

Applied Optimization Methods for Wireless Networks, Y. Thomas Hou, Yi Shi, Hanif D. Sherali,

    Cambridge Un. Press, 2014
 

Tentative Time-Table:

Oct..07           Introduction,

Oct..14           Mathematical Review (Chaps. 2-4)

Oct. 21           Mathematical Review (Chaps. 2-4)

Nov.04           Linear Programming (Chaps. 15-16)

Nov.11           Linear Programming (Chaps. 15-16)

Nov.18           Multivariable Calculus (Chap. 5), Unconstrained Optimization (Chap. 6)   

Dec. 02          Midterm Exam  

Dec. 09          Problems with Equality Constraints (Chap. 20)

Dec. 16          Problems with Inequality Constraints) (Chap. 21)

Dec. 23          Gradient Methods (Chap. 8),  Newton's Method (Chap. 9)

Dec. 30          Solving  Ax=b, Regression Analysis (Chap. 12)

Jan.. 06          Integer Linear Programming (Chap. 19)

Jan.. 13          Convex Optimization Problems (Chap. 22)