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In this study, we propose a new chaotic global optimization method using the Lagrangian method to solve a nonlinear constrained optimization problem. Firstly, we explain the convergence behavior of the first order method regarding convexity of the Lagrangian with respect to decision variables in terms of linear stability theory. Further, we propose a new optimization method in which the convergence...
As one of the global optimization methods to solve constrained optimization problems, we have proposed a chaotic Lagrangian method which utilizes chaotic search trajectories generated in a coupled gradient dynamics with respect to the augmented Lagrangian. We have confirmed the global search capability of the chaotic Lagrangian method. However, the chaotic Lagrangian method cannot be applied to a...
We have proposed "draining method (DM)". DM is based on the discrete gradient chaos model (DGCM) and the objective function transformation which is developed by the analysis of DGCM. Applying DM to typical benchmark problems, we have confirmed its superior global optimization capability. Besides, DM has a problem that we need to set objective function value (OFV) of global minima (or desired...
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