MSM 522 - Optimization

Institution:

University of Rochester

Subject:

Description:

This course introduces unconstrained and constrained optimization in RN. Theoretical topics include: convexity, Kuhn-Tucker conditions and Lagrangian duality. Algorithms include: equation solving (Newton), primal methods (gradient, variable metric, penalty and barrier, and successive quadratic programming), dual-ascent methods, and primal-dual methods (augmented Lagrangian).

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.rochester.edu

Phone Number:

(888) 822-2256

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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