We benchmark IPOP-CMA-ES, a restart Covariance Matrix Adaptation Evolution Strategy with increasing population size, with two step-size adaptation mechanisms, Two-Point Step-Size Adapation (TPA) and Median Success Rule (MSR), on the BBOB noiseless testbed. We then compare IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR to IPOP-CMA-ES with the standard step-size adaptation mechanism, Cumulative Step-size Adaptation (CSA). We conduct experiments for a budget of 10 5 times the dimension of the search space. As expected, the algorithms perform alike on most functions. However, we observe some relevant differences , the most significant being on the attractive sector function where IPOP-CMA-TPA and IPOP-CMA-CSA out-perform IPOP-CMA-MSR, and on the Rastrigin function where IPOP-CMA-MSR is the only algorithm to solve the function in all tested dimensions. We also observe that at least one of the three algorithms is comparable to the best BBOB-09 artificial algorithm on 13 functions.