Tree Based Differential Evolution

In recent years a new evolutionary algorithm for optimization in continuos spaces called Differential Evolution (DE) has developed. DE turns out to need only few evaluation steps to minimize a function. This makes it an interesting candidate for problem domains with high computational costs as for instance in the automatic generation of programs. In this paper a DE-based tree discovering algorithm called Tree based Differential Evolution (TreeDE) is presented. TreeDE maps full trees to vectors and represents discrete symbols by points in a real-valued vector space providing this way all arithmetical operations needed for the different DE schemes. Because TreeDE inherits the 'speed property' of DE, it needs only few evaluations to find suitable trees which produce comparable and better results as other methods.