  In this paper, we propose an efficient approximated rank one update for
covariance matrix adaptation evolution strategy (CMA-ES). It makes use of two
evolution paths as simple as that of CMA-ES, while avoiding the computational
matrix decomposition. We analyze the algorithms' properties and behaviors. We
experimentally study the proposed algorithm's performances. It generally
outperforms or performs competitively to the Cholesky CMA-ES.
