Quadratic optimization models and algorithms. One algorithm for linear bound constraints based on neural networks

被引：0

作者：

Popoviciu, Nicolae ^{[1
]}

Boncut, Mioara ^{[2
]}

机构：

[1] Univ Hyper, Bucharest, Romania

[2] Univ Luclan Blaga, Sibiu, Romania

来源：

PROCEEDINGS OF THE 9TH WSEAS INTERNATIONAL CONFERENCE ON NEURAL NETWORKS (NN' 08): ADVANCED TOPICS ON NEURAL NETWORKS | 2008年

关键词：

quadratic programming; quadratic optimization; linear bound constraints;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work contains a complete set of algorithms for several quadratic optimization problems. The problem constraints are very differently. For each type of constraint an appropriate algorithm is given. The algorithm for linear bound constraints is based on neural network [2] and uses a system of differential equations. In order to reduce the sensitivity and round off errors a preconditioning method is used. A great number of applications illustrate the algorithms.

引用

页码：26 / +

页数：3

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