New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds

• Published in: Mathematical programming Vol. 106; no. 3; pp. 403 - 421
• Main Authors: Dai, Yu-Hong, Fletcher, Roger
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer 01.07.2006; Springer Nature B.V
• Subjects: Algorithms; Applied sciences; Approximation; Computational mathematics; Digital Object Identifier; Exact sciences and technology; Mathematical programming; Operational research and scientific management; Operational research. Management science; Studies; Support vector machines; Projected gradient method; Diagonal matrix; Positive definite matrix; Vector support machine; Numerical method; Approximation algorithm; Quadratic programming; Adaptive method; Search algorithm; Constrained optimization; Mathematical programming; Large scale system

There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximation is provided for the case in which the Hessian matrix is diagonal and positive definite. To deal with the general cas...