The restarted Rosenbrock’s optimization algorithm is tested on the BBOB 2009 testbed. The algorithm turned out to be very efficient for functions with simple structure (independ...
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)....
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
New portable consumer embedded devices must execute multimedia applications (e.g., 3D games, video players and signal processing software, etc.) that demand extensive memory acces...
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...
Evolutionary problem decomposition techniques divide a complex problem into simpler subproblems, evolve individuals to produce subcomponents that solve the subproblems, and then a...
Heather Goldsby, Sherri Goings, Jeff Clune, Charle...
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
High–dimensional optimization problems appear very often in demanding applications. Although evolutionary algorithms constitute a valuable tool for solving such problems, their ...