# Global and superlinear convergence of inexact sequential quadratically constrained quadratic programming method for convex programming

Atsushi Kato, Yasushi Narushima, Hiroshi Yabe

Research output: Contribution to journalArticle

1 Citation (Scopus)

### Abstract

This paper is concerned with a sequential quadratically constrained quadratic programming (SQCQP) method for convex programming. The SQCQP method solves, at each iteration, a quadratically constrained quadratic programming subproblem whose objective function and constraints are quadratic approximations to the objective function and constraints of the original problem, respectively. We propose an inexact SQCQP method which solves inexactly the subproblem and prove its global and superlinear convergence properties.

Original language English 609-629 21 Pacific Journal of Optimization 8 3 Published - 2012 Jul 1 Yes

### Fingerprint

Superlinear Convergence
Convex optimization
Convex Programming
Global Convergence
Objective function
Convergence Properties
Iteration

### Keywords

• Convex programming
• Global convergence
• Superlinear convergence

### ASJC Scopus subject areas

• Control and Optimization
• Computational Mathematics
• Applied Mathematics

### Cite this

In: Pacific Journal of Optimization, Vol. 8, No. 3, 01.07.2012, p. 609-629.

Research output: Contribution to journalArticle

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