Differential evolution with Down-hill Simplex Method based on average distance

Differential Evolution (DE) is based on both an evolutionary strategy and a parallel direct search method employing a population. DE is an effective optimization method available for solving global optimization problem over continuous space. DE has a few control parameters that have to be set by users. This paper describes a new DE using Down-hill Simplex Method. Then we consider and examine average distance of a new DE. In addition we append a mechanism, using a proposed method or the other proposed method according to the average distance, to the new DE. The feasibility and advantage of the proposed DE are demonstrated through some numerical simulations using four different typical global optimization test problems.