Penalty function versus non-penalty function methods for constrained nonlinear programming problems

DOI10.1007/BF01584087zbMath0242.90051MaRDI QIDQ5653813

Garth P. McCormick

Publication date: 1971

Published in: Mathematical Programming (Search for Journal in Brave)

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items

Superlinearly convergent approximate Newton methods for LC\(^ 1\) optimization problems, Globally convergent version of Robinson's algorithm for general nonlinear programming problems without using derivatives, A globally and quadratically convergent algorithm for general nonlinear programming problems, Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear-programming algorithms, A quadratically-convergent algorithm for general nonlinear programming problems, On the global and superlinear convergence of a discretized version of Wilson's method, A recursive quadratic programming algorithm for semi-infinite optimization problems, Superlinearly convergent quasi-newton algorithms for nonlinearly constrained optimization problems, Minimization methods with constraints, A geometric method in nonlinear programming, Computational experience in sensitivity analysis for nonlinear programming

Cites Work

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