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 BFGS quasi-Newton method is benchmarked on the noisy BBOB-2009 testbed. A multistart strategy is applied with a maximum number of function evaluations of about 104 times the s...
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 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...
In this paper, a new framework for the tracking of closed curves is described. The proposed approach, formalized through an optimal control technique, enables a continuous trackin...