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Searched for: 1 subject found.
6.252[J] Nonlinear Optimization
(
)
(Same subject as 15.084[J])
Prereq: 18.06 and (18.100A, 18.100B, or 18.100Q)
Units: 4-0-8
Lecture: TR11-12.30 (E25-111) Recitation: F10.30 (34-303) or F11.30 (34-303) +final
Unified analytical and computational approach to nonlinear optimization problems. Unconstrained optimization methods include gradient, conjugate direction, Newton, sub-gradient and first-order methods. Constrained optimization methods include feasible directions, projection, interior point methods, and Lagrange multiplier methods. Convex analysis, Lagrangian relaxation, nondifferentiable optimization, and applications in integer programming. Comprehensive treatment of optimality conditions and Lagrange multipliers. Geometric approach to duality theory. Applications drawn from control, communications, machine learning, and resource allocation problems.
P. Parrilo
No textbook information available
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