Intro to Convex Optimization - AAE56100/IE56100
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.
Credit Hours: 3
Instructor(s): Dengfeng Sun
Phone: (765) 494-5718
Email: dsun@purdue.edu
Web: Instructor Homepage
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.
Prerequisites: Graduate standing or permission of the instructor.
Applied / Theory: 20 / 80
Homework: Worth 60% of grade
Projects: 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.
Exams: None
Textbooks: 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.