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Neural network approach to the solution of linear complementarity problems
Author(s) -
Osowski S.
Publication year - 1995
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.1660080605
Subject(s) - complementarity (molecular biology) , linear complementarity problem , mixed complementarity problem , complementarity theory , artificial neural network , quadratic programming , nonlinear complementarity problem , linear programming , mathematical optimization , nonlinear programming , computer science , nonlinear system , quadratic equation , optimization problem , mathematics , artificial intelligence , physics , geometry , genetics , quantum mechanics , biology
The paper presents the application of nonlinear neural optimization networks to solve the linear complementarity problem. Two different approaches are presented and investigated: one leading to linear and the second to quadratic optimization programming. The numerical results of illustrative examples are given and discussed.