Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Documents Associated With Scientific Events Year : 2015

Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed

Abstract

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.
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Dates and versions

hal-01323506 , version 1 (30-05-2016)

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Asma Atamna. Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed. GECCO (Companion), workshop on Black-Box Optimization Benchmarking (BBOB'2015), Jul 2015, Madrid, Spain. , ⟨10.1145/2739482.2768467⟩. ⟨hal-01323506⟩
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