Differential evolution with dither and annealed scale factor
Deepak Dawar, Simone A. Ludwig · 2014
Differential Evolution (DE) is a highly competitive and powerful real parameter optimizer in the diverse community of evolutionary algorithms. The performance of DE depends largely upon its control parameters and is quite sensitive to their appropriate settings. One of those parameters commonly known as scale factor or F, controls the step size of the vector differentials during the search. During the exploration stage of the search, large step sizes may prove more conducive while during the exploitation stage, smaller step sizes might become favorable. This work proposes a simple and effective technique that alters F in stages, first through random perturbations and then through the application of an annealing schedule. We report the performance of the new variant on 20 benchmark functions of varying complexity and compare it with the classic DE algorithm (DE/Rand/1/bin), two other scale factor altering variants, and state of the art, SaDE.