The existence of space filling curves opens the way to reducing multivariate optimization problems to the minimization of univariate functions. In this paper, we analyze the Hoelder continuity of space filling curves and exploit this property in the solution of global optimization problems. Subsequently, an algorithm for minimizing univariate Hoelder continuous functions is presented and analyzed. It is shown that the algorithm computes the approximate minimum with the guaranteed precision. The algorithm is tested on some types of two-dimensional functions
In this paper, a new filled function with only one parameter is proposed. The main advantages of the...
AbstractThe filled function method is an efficient approach for finding global minimizers of multi-d...
We propose new classes of globally convexized filled functions. Unlike the globally convexized fille...
AbstractIt is shown that, contrary to a claim of Törn and Zilinskas, it is possible to efficiently o...
Many real-world problems involve multivariate global optimization which can be difficult to solve. I...
Many real-world problems involve multivariate global optimization which can be difficult to solve. I...
In this paper, the global optimization problem min F(y) y∈S, with S=[a,b], a, b ∈ R^N, and F(y) sati...
In this paper the global optimization problem where the objective function is multiextremal and sati...
In this paper the global optimization problem where the objective function is multiextremal and sati...
In this paper, the Lipschitz global optimization problem is considered both in the cases of non-diff...
In this paper, the Lipschitz global optimization problem is considered both in the cases of non-diff...
In this paper, the global optimization problem miny∈SF(y) with S being a hyperinterval in RN and F(y...
In this paper the global optimization problem of a multiextremal function satisfying the Lipschitz ...
The problem of finding the global minimum of a real function on a set S ⊆ RN occurs in many real wor...
Global optimization is a field of mathematical programming dealing with finding global (absolute) mi...
In this paper, a new filled function with only one parameter is proposed. The main advantages of the...
AbstractThe filled function method is an efficient approach for finding global minimizers of multi-d...
We propose new classes of globally convexized filled functions. Unlike the globally convexized fille...
AbstractIt is shown that, contrary to a claim of Törn and Zilinskas, it is possible to efficiently o...
Many real-world problems involve multivariate global optimization which can be difficult to solve. I...
Many real-world problems involve multivariate global optimization which can be difficult to solve. I...
In this paper, the global optimization problem min F(y) y∈S, with S=[a,b], a, b ∈ R^N, and F(y) sati...
In this paper the global optimization problem where the objective function is multiextremal and sati...
In this paper the global optimization problem where the objective function is multiextremal and sati...
In this paper, the Lipschitz global optimization problem is considered both in the cases of non-diff...
In this paper, the Lipschitz global optimization problem is considered both in the cases of non-diff...
In this paper, the global optimization problem miny∈SF(y) with S being a hyperinterval in RN and F(y...
In this paper the global optimization problem of a multiextremal function satisfying the Lipschitz ...
The problem of finding the global minimum of a real function on a set S ⊆ RN occurs in many real wor...
Global optimization is a field of mathematical programming dealing with finding global (absolute) mi...
In this paper, a new filled function with only one parameter is proposed. The main advantages of the...
AbstractThe filled function method is an efficient approach for finding global minimizers of multi-d...
We propose new classes of globally convexized filled functions. Unlike the globally convexized fille...