A Modified Single-Parameter Filled Function Method for Unconstrained Global Optimization

The filled function method is an effective approach for finding the global minima of multimodal and multidimensional functions,and the constructed filled function is vital to the results of optimization.Therefor,by the thought of the literature[1],considering the optimization problem minf(x)x∈Rn,when f(x) is local Lipschitz continuous function,proposed a modified single-parameter filled function.It is easy to prove that this new filled function can keep filling properties easily relative to conventional filled functions,furthermore,its global convergent speed is rapid.The corresponding algorithm was also discussed in this paper.Numerical experience for 4 test functions indicate that the new method is better than the method in the reference.