Naive constant rank-type constraint qualifications for multifold second-order cone programming and semidefinite programming
Autor: | Leonardo M. Mito, Roberto Andreani, Thiago Parente da Silveira, Gabriel Haeser, Héctor Ramírez, D. O. Santos |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Semidefinite programming
Mathematical optimization 021103 operations research Control and Optimization OTIMIZAÇÃO NÃO LINEAR Augmented Lagrangian method Rank (computer programming) 0211 other engineering and technologies Mathematics::Optimization and Control 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Nonlinear programming Constraint (information theory) Optimization and Control (math.OC) Bellman equation 90C22 90C46 90C30 FOS: Mathematics Second-order cone programming Computer Science::Programming Languages 0101 mathematics Constant (mathematics) Mathematics - Optimization and Control Mathematics |
Zdroj: | Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP |
DOI: | 10.13140/rg.2.2.22766.02885 |
Popis: | The constant rank constraint qualification, introduced by Janin in 1984 for nonlinear programming, has been extensively used for sensitivity analysis, global convergence of first- and second-order algorithms, and for computing the derivative of the value function. In this paper we discuss naive extensions of constant rank-type constraint qualifications to second-order cone programming and semidefinite programming, which are based on the Approximate-Karush-Kuhn-Tucker necessary optimality condition and on the application of the reduction approach. Our definitions are strictly weaker than Robinson's constraint qualification, and an application to the global convergence of an augmented Lagrangian algorithm is obtained. Comment: An older version of this paper was separated in two, and SDP was included here. The first part can be found here: https://www.ime.usp.br/~ghaeser/nota-crcq-errata.pdf |
Databáze: | OpenAIRE |
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