Abstract. To improve the efficiency of the currently known evolutionary algorithms, we have proposed two complementary efficiency speed-up strategies in our previous research work ...
Evolutionary algorithms tend to produce solutions that are not evolvable: Although current fitness may be high, further search is impeded as the effects of mutation and crossover ...
Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...
Evolutionary multi-objective optimization deals with the task of computing a minimal set of search points according to a given set of objective functions. The task has been made e...
Rudolf Berghammer, Tobias Friedrich, Frank Neumann