On the Impact of a Small Initial Population Size in the IPOP Active CMA-ES with Mirrored Mutations on the Noiseless BBOB Testbed

International audienceActive Covariance Matrix Adaptation and Mirrored Mutations have been independently proposed as improved variants of the well-known optimization algorithm Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for numerical optimization. This paper investigates the impact of the algorithm's population size when both active covariance matrix adaptation and mirrored mutation are used in the CMA-ES. To this end, we compare the CMA-ES with standard population size $\lambda$, i.e., $\lambda = 4 + \lfloor 3\log(D) \rfloor$ with a version with half this population size where $D$ is the problem dimension