This paper introduces TestFul, a framework for testing stateful systems and focuses on object-oriented software. TestFul employs a hybrid multi-objective evolutionary algorithm, t...
The fundamental dichotomy in evolutionary algorithms is that between exploration and exploitation. Recently, several algorithms [8, 9, 14, 16, 17, 20] have been introduced that gu...
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 ...
Although there are some real world applications where the use of variable length representation (VLR) in Evolutionary Algorithm is natural and suitable, an academic framework is la...
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
A challenge in hybrid evolutionary algorithms is to define efficient strategies to cover all search space, applying local search only in actually promising search areas. This pape...
In empirical studies of Evolutionary Algorithms, it is usually desirable to evaluate and compare algorithms using as many different parameter settings and test problems as possible...
The investigation of evolutionary algorithms as adaptation schemes has a long history starting with Holland (1975). The Ising model from physics leads to a variety of different pr...
Patrick Briest, Dimo Brockhoff, Bastian Degener, M...
Geometrical place can be sometimes difficult to find by applying mathematical methods. Evolutionary algorithms deal with a population of solutions. This population (initially ran...
When applied to real-world problems, the powerful optimization tool of Evolutionary Algorithms frequently turns out to be too time-consuming due to elaborate fitness calculations t...