We propose a real-coded genetic algorithm that uses real parameter vectors as chromosomes, real parameters as genes, and real numbers as alleles.Expand

We show that the decision problem corresponding to optimizing random-model N-K fitness functions is NP-complete for K>1, and is polynomial for K=1.Expand

This paper addresses the problem of discovering the structure of a fitness function from binary strings to the reals under the assumption of bounded epistasis.Expand

We reinterpret the “No Free Lunch” theorem (NFL) to be a statement that is most naturally expressed in set-theoretic terms and that concerns symmetries inherent in Black Box Search without regard to any purpose.Expand

We study the search biases produced by GP subtree crossover when applied to linear representations, such as those used in linear GP or in variable length GAs.Expand

This paper continues the development, begun in Part I, of the relationship between the simple genetic algorithm and the Walsh transform and provides a framework that extends directly to higher cardinality alphabets.Expand

We investigate the relationship between the choice of representation used for a search problem and the genetic operators (crossover and mutation) that act upon it.Expand