Cooperative framework fireworks algorithm with covariance mutation

Chao Yu, Lingchen Kelley, Ying Tan

Abstract: Since fireworks algorithm (FWA) debuted in 2010, a dozen proposals of improvement for FWA had been published in an effort to enhance, refine and optimize accuracy while minimizing calculation speed and volume. In this paper, we introduce the covariance mutation operator into cooperative framework fireworks algorithm (CoFFWA) to create cooperative framework fireworks algorithm with covariance mutation (CoFFWA-CM) in order to solve the Congress on Evolutionary Computation (CEC 2016) competition functions on single objective optimization. The experimental results are calculated on all 10-, 30-, 50- and 100-dimensional functions.