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A filled function method for global optimization with inequality constraints. (English) Zbl 1433.90125
Summary: In this paper, we propose a new filled function method for finding a global minimizer of global optimization with inequality constraints. The proposed filled function is a continuously differentiable function with only one parameter. Then, we can use classical local optimization methods to find a better minimizer of the proposed filled function with a few parameter adjustment. The numerical experiments are made and the results show that the proposed filled function method is effective.
MSC:
90C26 Nonconvex programming, global optimization
90C56 Derivative-free methods and methods using generalized derivatives
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