ACM 113 - Introduction to Optimization

Institution:

California Institute of Technology

Subject:

Applied and Computational Mathematics

Description:

Unconstrained optimization: optimality conditions, line search and trust region methods, properties of steepest descent, conjugate gradient, Newton and quasi-Newton methods. Linear programming: optimality conditions, the simplex method, primal-dual interior-point methods. Nonlinear programming: Lagrange multipliers, optimality conditions, logarithmic barrier methods, quadratic penalty methods, augmented Lagrangian methods. Integer programming: cutting plane methods, branch and bound methods, complexity theory, NP complete problems. Instructor: Tropp.

Credits:

9.00

Credit Hours:

Prerequisites:

ACM 95/100 abc, ACM 11, 104 or equivalent, or instructor’s permission.

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.caltech.edu

Phone Number:

(626) 395-6811

Regional Accreditation:

Western Association of Schools and Colleges

Calendar System:

Quarter

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