Abstract
In this paper a sequential search method for finding the global maximum of an objective function is proposed. The method is applicable to an objective function of a single variable defined on a closed interval and such that some bound on its rate of change is available. The method is shown to be minimax. Computational aspects of the method are also discussed.
Index Terms
A Sequential Method Seeking the Global Maximum of a Function
Recommendations
A Sequential Convexification Method (SCM) for Continuous Global Optimization
A new method for continuous global minimization problems, acronymed SCM, is introduced. This method gives a simple transformation to convert the objective function to an auxiliary function with gradually `fewer' local minimizers. All Local minimizers ...
A Radial Basis Function Method for Global Optimization
We introduce a method that aims to find the global minimum of a continuous nonconvex function on a compact subset of \dR d. It is assumed that function evaluations are expensive and that no additional information is available. Radial basis function ...
A new constructing auxiliary function method for global optimization
A new auxiliary function method based on the idea which executes a two-stage deterministic search for global optimization is proposed. Specifically, a local minimum of the original function is first obtained, and then a stretching function technique is ...




Comments