Using the Ring Neighborhood Topology with Self-adaptive Differential Evolution

Differential Evolution (DE) is generally considered as a reliable, accurate, robust and fast optimization technique. DE has been successfully applied to solve a wide range of numerical optimization problems. However, the user is required to set the values of the control parameters of DE for each problem. Such parameter tuning is a time consuming task. Self-adaptive DE (SDE) is a new version of DE where parameter tuning is not required. The purpose of this paper is to investigate the performance of SDE using the ring neighborhood topology and to compare the results with other well-known approaches. The experiments conducted show that using the ring topology with SDE generally improves the performance of SDE in the benchmark functions.