Nonlinear Programming 4: Proceedings of the Nonlinear Programming Symposium 4Olvi L. Mangasarian, Robert R. Meyer, Stephen M. Robinson |
Contents
QPBased Methods for LargeScale Nonlinearly Constrained Optimization 557 | 57 |
Numerical Experiments with an Exact L Penalty Function Method | 99 |
An Iterative Linear Programming Algorithm Based on an Augmented | 131 |
Copyright | |
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active algorithm applied approach approximation assume bound calculation called closed column computed conjugate gradient consider constraints contains convergence convex corresponding defined denote depends derivative descent described determine direction ellipsoid equal equations estimate evaluations exact example exists experience fact factorization feasible finite follows function given gives Hence Hessian holds implies independent inequality interval iteration Journal least Lemma linear linear programming Mathematical Programming matrix method minimization multiplier nonlinear programming Note obtained Operations optimization parameter penalty plane polynomial possible Powell problem procedure programming projection Proof prove reduced Report Research satisfied sequence simplex method solution solving space step subgradient Suppose Table techniques Theorem theory tion University update upper variables vector zero