Exponential Filled Function Method for Solving Multi-dimension Global Optimization

Abstract

The filled function technique is a highly efficient and successful approach for addressing global optimization problems. The performance of the filled function relies on parameters and attributes such as continuity, differentiability, and speed rate of reaching the optimal solution. This paper introduces a continuously differentiable filled function with a single parameter, and theoretical arguments are offered to demonstrate its features. A filled function method is built based on the suggested function to solve unconstrained global optimization issues. The numerical results of the suggested filled function on various test functions demonstrate the efficiency of this method.