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Main Authors: Chieu, Nguyen Huy, Trang, Nguyen Thi Quynh, Yen, Nguyen Thi Hai
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.00365
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author Chieu, Nguyen Huy
Trang, Nguyen Thi Quynh
Yen, Nguyen Thi Hai
author_facet Chieu, Nguyen Huy
Trang, Nguyen Thi Quynh
Yen, Nguyen Thi Hai
contents The constant rank constraint qualification (CRCQ) for second-order cone programs, introduced by Andreani et al. in [Math. Program. 202 (2023), 473 - 513], shares some desirable properties with its classical nonlinear programming counterpart; specifically, it guarantees strong second-order necessary conditions for optimality, and is independent of the Robinson constraint qualification. However, unlike the classical version, this new CRCQ can fail in the linear case, and it is unclear whether CRCQ implies the metric subregularity constraint qualification (MSCQ). The aim of this paper is to examine the CRCQ for second-order cone programs in the linear setting. First, we show that the facial constant rank property, which is a key requirement for the validity of CRCQ, does not always hold in this context. Then, we derive a necessary and sufficient condition for a feasible point to satisfy this property. After that, we establish an easily verifiable characterization of CRCQ. Finally, utilizing this characterization, we prove that CRCQ and MSCQ are equivalent.
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publishDate 2026
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spellingShingle Revisiting the Constant-Rank Constraint Qualification for Second-Order Cone Programs
Chieu, Nguyen Huy
Trang, Nguyen Thi Quynh
Yen, Nguyen Thi Hai
Optimization and Control
The constant rank constraint qualification (CRCQ) for second-order cone programs, introduced by Andreani et al. in [Math. Program. 202 (2023), 473 - 513], shares some desirable properties with its classical nonlinear programming counterpart; specifically, it guarantees strong second-order necessary conditions for optimality, and is independent of the Robinson constraint qualification. However, unlike the classical version, this new CRCQ can fail in the linear case, and it is unclear whether CRCQ implies the metric subregularity constraint qualification (MSCQ). The aim of this paper is to examine the CRCQ for second-order cone programs in the linear setting. First, we show that the facial constant rank property, which is a key requirement for the validity of CRCQ, does not always hold in this context. Then, we derive a necessary and sufficient condition for a feasible point to satisfy this property. After that, we establish an easily verifiable characterization of CRCQ. Finally, utilizing this characterization, we prove that CRCQ and MSCQ are equivalent.
title Revisiting the Constant-Rank Constraint Qualification for Second-Order Cone Programs
topic Optimization and Control
url https://arxiv.org/abs/2604.00365