Notice: For the latest information and guidance on Purdue's response to COVID-19 please visit:

Intro to Convex Optimization


Credit Hours:


Learning Objective:

On completing this course, the student shall be able to:
1) Understand basics of convex analysis and convex optimization problems.
2) Understand and develop basic algorithms of convex optimization and their complexities.
3) Apply convex optimization to solve engineering problems.


This course aims to introduce students basics of convex analysis and convex optimization problems, basic algorithms of convex optimization and their complexities, and applications of convex optimization in aerospace engineering. This course also trains students to recognize convex optimization problems that arise in scientific and engineering applications, and introduces software tools to solve convex optimization problems.
Course Syllabus

Topics Covered:


Graduate standing or permission of the instructor.

Applied / Theory:

20 / 80


Worth 60% of grade


The project will be decided with the instructor in the mid of the semester. it will be relevant to theory or application of convex optimization.




Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.
Convex Optimization, by Stephen Boyd and Lieven Vandenberghe, Cambridge University Press, free downloadable from Prof. Stephen Boyd's webpage at Stanford University.

Computer Requirements:

Any O/S will be appropriate. Require at least one programming language, including byt not limited to Matlab, Python, C/C+, and Java.

ProEd Minimum Requirements:


Tuition & Fees: