Mutation-Selection Algorithm: a Large Deviation Approach
Paul Albuquerque; Christian Mazza Dept. of Computer Science, University of Geneva, 24 rue Général–Dufour, CH-1211 Geneva 4, SwitzerlandLaboratoire de Probabilités, Université Claude Bernard Lyon-I, 43 Bd du 11–Novembre-1918, 69622 Villeurbanne Cedex, France
We consider a two-operator mutation–selection algorithm designed to optimize a fitness function on the space of fixed length binary strings. Mutation acts as in classical genetic algorithms, while the fitness-based selection operates through a Gibbs measure (Boltzmann selection). The selective pressure is controlled by a temperature parameter. We provide a mathematical analysis of the convergence of the algorithm, based on the ...
Get Foundations of Genetic Algorithms 2001 (FOGA 6) now with O’Reilly online learning.
O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.