Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Gaphyl: An Evolutionary Algorithms Approach For The Study Of Natural Evolution
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Schema theory for genetic programming with one-point crossover and point mutation
Evolutionary Computation
Finding consensus trees by evolutionary, variable neighborhood search, and hybrid algorithms
Proceedings of the 10th annual conference on Genetic and evolutionary computation
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In some cases, evolutionary algorithms represent individuals as typical binary trees with n leaves and n-1 internal nodes. When designing a crossover operator for a particular representation and application, it is desirable to quantify the operator's destructiveness in order to estimate its effectiveness at using building blocks. For the case of binary tree representations, we present a novel approach for empirically estimating the destructiveness of any crossover operator by computing and summarizing the distribution of Robinson-Foulds distances from the parent to the entire neighborhood of possible children. We demonstrate the approach by quantifying the destructiveness of a popular tree-based crossover operator as applied to the problem of phylogenetic inferencing. We discuss the benefits and limitations of the destructiveness metric.