Rossi, ClaudioAbderrahim Fichouche, MohamedDíaz Cabrera, Julio César2010-12-202010-12-202008-03Evolutionary Computation, 2008, v. 16, n. 1, p. 1-301063-6560https://hdl.handle.net/10016/984830 pages, 23 figures.The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a time-changing fitness landscape. In this paper we compare different techniques for integrating motion information into an evolutionary algorithm, in the case it has to follow a time-changing optimum, under the assumption that the changes follow a nonrandom law. Such a law can be estimated in order to improve the optimum tracking capabilities of the algorithm. In particular, we will focus on first order dynamical laws to track moving objects. A vision-based tracking robotic application is used as testbed for experimental comparison.application/pdfengEvolutionary algorithmsVision-based trackingDynamic optimization problemTime-varying fitness functionresearch articleRobótica e Informática Industrial10.1162/evco.2008.16.1.1open access