New Particle Swarm Optimization (PSO) methods for dynamic and noisy function optimization are studied in this paper. The new methods are based on the hierarchical PSO (H-PSO) and a...
In this work we evaluate a Particle Swarm Optimizer hybridized with Differential Evolution and apply it to the BlackBox Optimization Benchmarking for noisy functions (BBOB 2009)....
Dealing with imprecise information is a common characteristic in real-world problems. Specifically, when the source of the information are physical sensors, a level of noise in t...
Abstract. In practical applications evaluating a fitness function is frequently subject to noise, i. e., the “true fitness” is disturbed by some random variations. Evolutiona...