Using Dynastic Exploring Recombination to Promote Diversity in Genetic Search

A family of recombination operators is studied in this work. These operators are based on keeping and using certain information about the past evolution of the algorithm to guide the recombination process. Within this framework, several recombination operators are specifically designed to preserve diversity within the population, while avoiding implicit mutations. The empirical evaluation of these operators on instances of two test problems (k-EMP and permutation flowshop) shows an improvement of the results with respect to other classical operators. This improvement seems to related to the increasing degree of epistasis of the problem

Two broad classes of functions for which a no free lunch result does not hold

Abstract. We identify classes of functions for which a No Free Lunch result does and does not hold, with particular emphasis on the relationship between No Free Lunch and problem description length. We show that a NFL result does not apply to a set of functions when the description length of the functions is sufficiently bounded. We consider sets of functions with non-uniform associated probability distributions, and show that a NFL result does not hold if the probabilities are assigned according either to description length or to a Solomonoff-Levin distribution. We close with a discussion of the conditions under which NFL can apply to sets containing an infinite number of functions.