Examples of ill-behaved central paths in convex optimization

DOI10.1007/s10107-003-0460-0zbMath1079.90099OpenAlexW2009666506MaRDI QIDQ1777216

Clóvis C. Gonzaga, Gilbert, Jean Charles, Elizabeth W. Karas

Publication date: 12 May 2005

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

Full work available at URL: https://doi.org/10.1007/s10107-003-0460-0

zbMATH Keywords

Nonlinear programmingConvex optimizationPenalty function methodsInterior point algorithmCentral path

Mathematics Subject Classification ID

Convex programming (90C25) Interior-point methods (90C51)

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Analysis of some interior point continuous trajectories for convex programming, Apart sets and functions: an application to the stability of penalized optimization problems, Log-Barrier Interior Point Methods Are Not Strongly Polynomial, IFORS' Operational Research Hall of Fame: Clóvis Caesar Gonzaga, Dual convergence for penalty algorithms in convex programming, Primal-dual relationship between Levenberg-Marquardt and central trajectories for linearly constrained convex optimization, Generalization: One technique of computational and applied mathematical methodology, The Convergent Generalized Central Paths for Linearly Constrained Convex Programming, On some properties and an application of the logarithmic barrier method, On the solution uniqueness characterization in the L1 norm and polyhedral gauge recovery

Uses Software

• TRICE

Cites Work

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