A partly time and space linear CMA-ES is benchmarked on the BBOB-2009 noiseless function testbed. This algorithm with a multistart strategy with increasing population size solves ...
We benchmark an independent-restart-(1+1)-CMA-ES on the BBOB-2009 noisy testbed. The (1+1)-CMA-ES is an adaptive stochastic algorithm for the optimization of objective functions d...
A partly time and space linear CMA-ES is benchmarked on the BBOB-2009 noisy function testbed. This algorithm with a multistart strategy with increasing population size solves 10 f...
The (1+1)-ES with one-fifth success rule is one of the first and simplest stochastic algorithm proposed for optimization on a continuous search space in a black-box scenario. In...
We benchmark the pure random search algorithm on the BBOB 2009 noise-free testbed. Each candidate solution is sampled uniformly in [−5, 5]D , where D denotes the search space di...