Coevolution is a powerful tool in evoltionary computing that mitigate some of its endemic problems, namely stagnation in local optima and lack of convergence in high dimensionality problems. Since its inception in 1990, there are multiple articles that have contributed greatly to the development and improvement of the coevolutionary techniques. In this report we review some of those landmark ar...

This paper presents some ideas about an approach which aims at extending existing methodologies for functional testing. Experience in automotive applications has shown that when selecting parameters for functional testing, many times a tester has equivalence classes in mind. Instead of losing valuable information in the process, support should be given to make them manageable. The proposed appr...

We introduce the concept of fruitful regions in a dynamic routing context: regions that have a high potential of generating loads to be transported. The objective is to maximise the number of loads transported, while keeping to capacity and time constraints. Loads arrive while the problem is being solved, which makes it a real-time routing problem. The solver is a self-adaptive evolutionary alg...

WEKA has recently become a very referenced DM tool. In spite of all the functionality it provides, it does not include any framework for the development of evolutionary algorithms. An evolutionary computation framework is JCLEC, which has been successfully employed for developing several EAs. The combination of both may lead in a mutual benefit. Thus, this paper proposes an intermediate layer t...

This section presents a brief but comprehensive summary of the history of evolutionary computation, starting with the ground-breaking work of the 1950s, tracing the rise and development of the three primary forms of evolutionary algorithms (evolution strategies, evolutionary programming and genetic algorithms), and concluding with the present time, in which a more unified view of the field is e...