A first-order interior-point method for linearly constrained smooth optimization

DOI10.1007/s10107-009-0292-7zbMath1216.49028OpenAlexW1970911233MaRDI QIDQ535018

Paul Tseng, Immanuel M. Bomze, Werner Schachinger

Publication date: 11 May 2011

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10107-009-0292-7

zbMATH Keywords

global convergenceinterior-point methodreplicator dynamicslinearly constrained optimizationaffine scalingsublinear convergence rate

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Quadratic programming (90C20) Numerical methods based on nonlinear programming (49M37) Interior-point methods (90C51)

Related Items

Analysis of some interior point continuous trajectories for convex programming, An affine scaling method using a class of differential barrier functions: primal approach, Standard bi-quadratic optimization problems and unconstrained polynomial reformulations, A partial first-order affine-scaling method, A strategy of global convergence for the affine scaling algorithm for convex semidefinite programming, A Smoothing Active Set Method for Linearly Constrained Non-Lipschitz Nonconvex Optimization, An affine scaling method for optimization problems with polyhedral constraints, Hessian Barrier Algorithms for Linearly Constrained Optimization Problems

Uses Software

• MINOS
• minpack

Cites Work

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