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__TOC__ == Course Information == {| style="width:60%;" border="1" cellpadding="2" cellspacing="0" align="center" |+ ! style="background:#cccc99;color:black;width:20%;" | Course | Optimization Theory (Lectures in English) |- ! style="background:#cccc99;color:black;width:20%;" | Department | Electronics Engineering |- ! style="background:#cccc99;color:black;width:20%;" | Course Number | G14741 |- ! style="background:#cccc99;color:black;width:20%;" | Hours | 3 hours (MW 9:30-10:45AM) |- ! style="background:#cccc99;color:black;width:20%;" | Credits | 3.0 credits |- ! style="background:#cccc99;color:black;width:20%;" | Instructor | Prof. [[Faculty:Hyunggon Park|Hyunggon Park]] |- ! style="background:#cccc99;color:black;width:20%;" | Office | Engineering A Bldg. 514 |- ! style="background:#cccc99;color:black;width:20%;" | Tel. | 3277-3896 |- ! style="background:#cccc99;color:black;width:20%;" | Email | [mailto:hyunggon.park@ewha.ac.kr hyunggon.park@ewha.ac.kr] |} == Course Objectives == Concentrates on recognizing and solving linear and convex optimization problems that arise in engineering. Linear programming, duality, simplex method, convex sets, functions, and optimization problems. Optimality conditions, duality theory, theorems of alternative, and applications. Applications to signal processing, control, digital and analog circuit design, computational geometry, statistics, and mechanical engineering. == Texts and References == * Textbooks ** S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press. (Not mandatory) * References ** D. Bertsimas and J. N. Tsitsiklis, Introduction to linear optimization (Athena Scientific). ** D. Bertsekas, Nonlinear Programming, Athena Scientific. == Course Structures and Teaching Methods == Lectures == Course Requirements and Assignments == Students are required to do their homework. == Evaluation and Grades == # Homework (20%) # Midterm Exam (30%) # Final Exam (50%) == Tentative Course Outline == A tentative list of the covered topics: * Review of basic linear algebra * Geometry of linear programming problems * Linear programming problems * Duality * The simplex method * Convex set, convex functions * Convex optimization problems * Numerical linear algebra * Other related topics

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