A New Parameter-Free Filled Function for Unconstrained Global Optimization

Many real life problems can be modeled as nonlinear global optimization problems. Such problems often have multiple local minima and thus require global optimization methods. One of the more recent global optimization tools is known as the filled function method which is a promising way used in unconstrained global optimization. Several filled functions with one or two parameters have already been suggested in the literatures. A new parameter-free filled function different from An [2004, Journal of Shanghai University] is proposed in this paper. The algorithm and numerical results of test functions are reported for comparison.