Quadratic optimization models and algorithms: one algorithm for linear bound constraints based on neural networks

Authors:
Nicolae Popoviciu;Mioara Boncut
Affiliations:
University Hyperion of Bucharest, Romania;University Lucian Blaga of Sibiu, Romania
Venue:
NN'08 Proceedings of the 9th WSEAS International Conference on Neural Networks
Year:
2008

Citing 3
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Algorithms of choosing the pre-conditioner matrix for quadratic programming with linear bound constraints

NN'08 Proceedings of the 9th WSEAS International Conference on Neural Networks

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Abstract

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.