Journal Article10.1007/S40314-016-0407-8
A filled function method for global optimization with inequality constraints
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TL;DR: A new filled function method for finding a global minimizer of global optimization with inequality constraints, which is a continuously differentiable function with only one parameter is proposed.
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Abstract: 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.
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Citations
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References
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A Filled Function Method with One Parameter for Constrained Global Optimization
TL;DR: The definition of the filled function for constrained problem is given and it is proved it is really a filled function under some mild assumptions and a new algorithm is presented according to the theoretical analysis.
4
The Tunneling Algorithm for the Global Minimization of Functions
A. V. Levy,A. Montalvo +1 more
TL;DR: In this paper, the authors considered the problem of finding the global minima of a function and presented an algorithm composed of a sequence of subsequences of c-minima functions.
Handbook Of Test Problems In Local And Global Optimization
Andreas Ritter
- 01 Jan 2016
TL;DR: Thank you for reading handbook of test problems in local and global optimization.
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TL;DR: The case of Lipschitz-continuous functions is studied in detail and an analogy with iterative and relaxation methods for the solution of a system of linear equations is made.
Finding Global Minima with a Computable Filled Function
TL;DR: This paper proposes a new filled function that needs only one parameter and does not include exponential terms, and has better computability than the traditional ones.