Nov 21, 2024  
2020-2021 Graduate Catalog 
    
2020-2021 Graduate Catalog [ARCHIVED CATALOG]

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MATH 651 - Optimization Algorithms

[3]
Design and analysis of algorithms for linear and non-linear optimization; first-order numerical methods for unconstrained optimization (line-search methods, steepest-descent method, trust-region method, conjugate-gradient method, quasi-Newton methods, methods for large scale problems); Newton’s method; numerical methods for linear programming (simplex methods, interior-point methods); numerical methods for constrained optimization (penalty, barrier, and augmented-Lagrangian methods, sequential quadratic programming method).
Prerequisite: Prerequisite: MATH 221, MATH 251, or consent of instructor. MATH 650  recommended.



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