A brief survey of differential evolution on Graphic Processing Units

Differential evolution is an efficient populational meta-heuristic optimization algorithm that has been applied to many difficult real world problems. Due to the relative simplicity of its operations and real encoded data structures, it is suitable for a parallel implementation on multicore systems and on Graphic Processing Units (GPUs) that nowadays reach peak performance of hundreds and thousands of giga FLOPS (floating-point operations per second). This study provides a brief survey of current state-of-the-art research on differential evolution in the GPU environment.