Evaluating the performance of SHADE on CEC 2013 benchmark problems
Ryoji Tanabe, Alex S. Fukunaga · 2013
This paper evaluates the performance of Success-History based Adaptive DE (SHADE) on the benchmark set for the CEC2013 Competition on Real-Parameter Single Objective Optimization. SHADE is an adaptive differential algorithm which uses a history-based parameter adaptation scheme. Experimental results on 28 problems from the CEC2013 benchmarks for 10, 30, and 50 dimensions are presented, including measurements of algorithmic complexity. In addition, we investigate the parameter adaptation behavior of SHADE on these instances.