Mirrored variants of the (1, 2)-CMA-ES compared on the noiseless BBOB-2010 testbed

Derandomization by means of mirroring has been recently introduced to enhance the performances of (1, λ)-EvolutionStrategies (ESs) with the aim of designing fast robust local search stochastic algorithms. This paper compares on the BBOB-2010 noiseless benchmark testbed two variants of the (1,2)-CMA-ES where the mirroring method is implemented. Independent restarts are conducted till a total budget of 104 D function evaluations per trial is reached, where D is the dimension of the search space. The results show that the improved variants increase the success probability on 5 (respectively 7) out of 24 test functions in 20D and at the same time are significantly faster on 9 (10) functions in 20D by a factor of about 2–3 (2–4) for a target value of 10−7 while in no case, the baseline (1,2)-CMA-ES is significantly faster on any tested target function value in 5D and 20D. Categories and Subject Descriptors

• Type: Conference
• Year: 2010
• Where: GECCO
• Authors: Anne Auger, Dimo Brockhoff, Nikolaus Hansen
• Keywords: BBOB-2010 Noiseless Benchmark, GECCO 2010, Mirroring Method, Optimization, Search Stochastic Algorithms