A new feasible descent primal-dual interior point algorithm for nonlinear inequality constrained optimization

DOI10.1016/j.apm.2009.10.012zbMath1193.90195OpenAlexW2087912111WikidataQ56935332 ScholiaQ56935332MaRDI QIDQ988435

Jin-Bao Jian, Hua-Qin Pan

Publication date: 26 August 2010

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2009.10.012

zbMATH Keywords

global convergenceconstrained optimizationinterior point methodsuperlinear convergenceworking set

Mathematics Subject Classification ID

Nonlinear programming (90C30) Interior-point methods (90C51)

Related Items (1)

A strongly sub-feasible primal-dual quasi interior-point algorithm for nonlinear inequality constrained optimization

Uses Software

• SNOPT

Cites Work

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• SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

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