2014•Journal of Computational and Applied MathematicsRequires access

A superlinearly convergent SQP method without boundedness assumptions on any of the iterative sequences

JianJin-bao, ChenQiao-fang, HuangZong-wen

Abstract

This paper is aimed to present a new sequential quadratic programming (SQP) algorithm for finding a solution to nonlinear constrained programming problems with weak conditions, where the improved d...

About this research paper

What this paper is about

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Mathematics, Sequential quadratic programming, Mathematical optimization, Iterative method, Applied mathematics, Quadratic programming

Back to paper search Browse research topics Original source

A superlinearly convergent SQP method without boundedness assumptions on any of the iterative sequences — Research Paper | ScholarLens