BUSCADOR RECOLECTA

Cellular evolutionary algorithms (cEAs) use structured populations whose evolutionary cycle is governed by local interactions among individuals. This helps to prevent the premature convergence to local optima that usually takes place in panmictic populations. The present work extends cEAs by means of a message passing phase whose main effect is a more effective exploration of the search space. The mutated offspring that potentially replaces the original individual under cEAs is considered under message passing cellular evolutionary algorithms (MPcEAs) as a message sent from the original individual to itself. In MPcEAs, unlike in cEAs, a new message is sent from the original individual to each of its neighbors, representing a neighbor’s mutated offspring whose second parent is selected from the neighborhood of the original individual. Thus, every individual in the population ultimately receives one additional candidate for replacement from each of its neighbors rather than having a unique candidate. Experimental tests conducted in the domain of real function optimization for continuous search spaces show that, in general, MPcEAs significantly outperform cEAs in terms of effectiveness. Specifically, the best solution obtained through MPcEAs has an importantly improved fitness quality in comparison to that obtained by cEAs.

Fractals are a family of shapes formed by irregular and fragmented patterns. They can be classified into two main groups: geometric and algebraic. Whereas the former are characterized by a fixed geometric replacement rule, the latter are defined by a recurrence function in the complex plane. The classical method for visualizing algebraic fractals considers the sequence of complex numbers originated from each point in the complex plane. Thus, each original point is colored depending on whether its generated sequence escapes to infinity. The present work introduces a novel visualization method for algebraic fractals. This method colors each original point by taking into account the complex number with minimum modulus within its generated sequence. The advantages of the novel method are twofold: on the one hand, it preserves the fractal view that the classical method offers of the escape set boundary and, on the other hand, it additionally provides interesting visual details of the prisoner set (the complement of the escape set). The novel method is comparatively evaluated with other classical and non-classical visualization methods of fractals, giving rise to aesthetic views of prisoner sets.

The evacuation problem is usually addressed by assuming homogeneous media where pedestrians move freely in the presence of several exits and obstacles. From a more general perspective, this work considers heterogeneous media in which the velocity of pedestrians depends on their location. We use cellular automata with a floor field that indicates promising movements to pedestrians and, in this context, we extend two competitive evacuation methods in order for them to be applied to heterogeneous media: the Fast Marching Method and the Fast Evacuation Method. Furthermore, we evaluate the performance that these two methods exhibit over different simulated scenarios characterized by the presence of heterogeneous media. The resulting winning method in terms of evacuation effectiveness is greatly influenced by the particular problem being simulated.