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2008 Eighth International Conference on Hybrid Intelligent Systems
A Neurogenetic Approach and its Application to Constrained Nonlinear Convex Optimization Problems with Joint and Disjoint Feasible Regions
September 10-September 12
ISBN: 978-0-7695-3326-1
| ASCII Text | x | ||
| Fabiana Cristina Bertoni, Ivan Nunes da Silva, Matheus Giovanni Pires, "A Neurogenetic Approach and its Application to Constrained Nonlinear Convex Optimization Problems with Joint and Disjoint Feasible Regions," Hybrid Intelligent Systems, International Conference on, pp. 90-95, 2008 Eighth International Conference on Hybrid Intelligent Systems, 2008. | |||
| BibTex | x | ||
| @article{ 10.1109/HIS.2008.162, author = {Fabiana Cristina Bertoni and Ivan Nunes da Silva and Matheus Giovanni Pires}, title = {A Neurogenetic Approach and its Application to Constrained Nonlinear Convex Optimization Problems with Joint and Disjoint Feasible Regions}, journal ={Hybrid Intelligent Systems, International Conference on}, volume = {0}, year = {2008}, isbn = {978-0-7695-3326-1}, pages = {90-95}, doi = {http://doi.ieeecomputersociety.org/10.1109/HIS.2008.162}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Hybrid Intelligent Systems, International Conference on TI - A Neurogenetic Approach and its Application to Constrained Nonlinear Convex Optimization Problems with Joint and Disjoint Feasible Regions SN - 978-0-7695-3326-1 SP90 EP95 A1 - Fabiana Cristina Bertoni, A1 - Ivan Nunes da Silva, A1 - Matheus Giovanni Pires, PY - 2008 KW - Nonlinear optimization KW - Hopfield Network KW - Genetic Algorithm VL - 0 JA - Hybrid Intelligent Systems, International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HIS.2008.162
A neurogenetic approach is presented for solving constrained nonlinear convex optimization problems with joint and disjoint feasible regions. More specifically, a modified Hopfield neural network is associated with a genetic algorithm in order to treat optimization and constraint terms in different stages with no interference with each other. Under the condition that the objective function is convex and the constraint set is convex, the proposed approach is proved to be stable in the sense of Lyapunov and globally convergent to the equilibrium points, which represent feasible solutions for constrained nonlinear convex optimization problems. Simulation results are provided to demonstrate the performance of the proposed approach.
Index Terms:
Nonlinear optimization, Hopfield Network, Genetic Algorithm
Citation:
Fabiana Cristina Bertoni, Ivan Nunes da Silva, Matheus Giovanni Pires, "A Neurogenetic Approach and its Application to Constrained Nonlinear Convex Optimization Problems with Joint and Disjoint Feasible Regions," his, pp.90-95, 2008 Eighth International Conference on Hybrid Intelligent Systems, 2008
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