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Jan 02, 2025
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EECS 260: Optimization
[4.0 units]
Introduction of theory and numerical methods for continuous multivariate optimization (unconstrained and constrained), including: line-search and trust-region strategies; conjugate-gradient, Newton, quasi-Newton and large-scale methods; linear programming; quadratic programming; penalty and augmented Lagrangian methods; sequential quadratic programming; and interior-point methods.
Prerequisite: MATH 023 , MATH 024 , MATH 141 or consent of instructor. Normal Letter Grade only. Laboratory included.
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