Differential evolution using a localized Cauchy mutation operator

In the present work, we propose a new variant of basic DE algorithm called CMDE-G which uses Cauchy mutation (CM) operator. In this algorithm, at the end of every generation, CM is applied as a local search mechanism to explore the neighborhood of the best individual in the population. The performance of CMDE-G algorithm is analyzed on a set of 10 standard benchmark problems and four nontraditional composite functions. Simulation results show that the proposed algorithm helps in improving the solution quality besides maintaining a good convergence rate.