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Analog neural nonderivative optimizers
(Institute of Electrical and Electronics Engineers (IEEE), 1998-07-01)
Continuous-time neural networks for solving convex nonlinear unconstrained;programming problems without using gradient information of the objective function are proposed and analyzed. Thus, the proposed networks are ...
Analog neural nonderivative optimizers
(Institute of Electrical and Electronics Engineers (IEEE), 1998-07-01)
Continuous-time neural networks for solving convex nonlinear unconstrained;programming problems without using gradient information of the objective function are proposed and analyzed. Thus, the proposed networks are ...
Free time and mixed constrained optimal control problems
(2010-12-01)
We consider free time optimal control problems with pointwise set control constraints u(t) ∈ U(t). Here we derive necessary conditions of optimality for those problem where the set U(t) is defined by equality and inequality ...
Analog neural nonderivative optimizers
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
Derivative-free methods for nonlinear programming with general lower-level constraints
(Soc Brasileira Matematica Aplicada & ComputacionalSao Carlos SpBrasil, 2011)
Inexact Restoration method for nonlinear optimization without derivatives
(Elsevier Science, 2015-05)
A derivative-free optimization method is proposed for solving a general nonlinear programming problem. It is assumed that the derivatives of the objective function and the constraints are not available. The new method is ...
Free time and mixed constrained optimal control problems
(2010-12-01)
We consider free time optimal control problems with pointwise set control constraints u(t) ∈ U(t). Here we derive necessary conditions of optimality for those problem where the set U(t) is defined by equality and inequality ...