Catalog Description: Convex optimization as a systematic approximation tool for hard decision problems. Approximations of combinatorial optimization problems, of stochastic programming problems, of robust optimization problems (i.e., with optimization problems with unknown but bounded data), of optimal control problems. Quality estimates of the resulting approximation. Applications in robust engineering design, statistics, control, finance, data mining, operations research.

Units: 3

Also Offered As: INDENG C227B, ELENG C227C

Prerequisites: 227A or consent of instructor.

Formats:
Fall: 3.0 hours of lecture per week
Spring: 3.0 hours of lecture per week

Grading Basis: Student Option

Final Exam Status: Yes

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