Abstract
Nonlinear optimization is the foundation of multiobjective programming. In this paper, our focus is augmented Lagrange multiplier (ALM) method which is employed in constrained nonlinear optimization propositions. A dynamic approach is raised for minimization subproblem in augmented Lagrange multiplier method and a neural network alternative algorithm for general constrained programming is proposed.
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