Nonlinear Optimization Models and Solving Algorithms based on Appropriate Neural Networks

被引：0
|
作者：
Popoviciu, Nicolae [1 ]
机构：
[1] Univ Hyper Bucharest, Bucharest, Romania
来源：
SSE '09: PROCEEDINGS OF THE 11TH WSEAS INTERNATIONAL CONFERENCE ON SUSTAINABILITY IN SCIENCE ENGINEERING | 2009年
关键词：
Quadratic programming; quadratic optimization; linear bound constraints; nonlinear convex optimization; nonlinear convex bounded optimization; BOUND CONSTRAINTS;
D O I：
暂无
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
This work contains a complete set of algorithms for several quadratic and nonlinear optimization problems. The problem constraints are very differently. For each type of constraint an appropriate algorithm is given. The algorithms for linear bound constraints and nonlinear optimization are based on neural networks [2] [11] 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 numerical applications illustrates the algorithms.
引用
收藏
页码：431 / +
页数：2
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