Linear and Nonlinear Programming: Second Edition

By D. Luenberger. 2003

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Some Notes on Alternating Optimization (2002, methodology): “More typically, we resort to computational methods such as gradient-based descent in all variables [12-14]; and gradient-based alternating descent (AO) on subsets of the variables [15-17], A relatively new set of interesting techniques that eschew the use of optimality conditions from calculus are b”
Improving amplify-and-forward relay networks: optimal power allocation versus selection (2006, methodology): “also be easily verified by the Kuhn-Tucker conditions [ 11 ].”
Pool Strategy of a Price-Maker Wind Power Producer (2013, background): “Indeed, KKT conditions are necessary and sufficient for optimality if the lower-level problems are convex and their constraints satisfy some regularity conditions [20].”
Gaussian Processes for history-matching: application to an unconventional gas reservoir (2017, methodology): “(a) Quasi-Newton methods Broyden-Fletcher-GoldfarbShanno (BFGS) algorithm is a quasi-Newton approach for approximation of Hessian matrix in nonlinear optimization problem [79].”