High Probability Mutation and Error Thresholds in Genetic Algorithms

Abstract

Error Threshold is a concept from molecular biology that has been introduced [G. Ochoa (2006) Error Thresholds in Genetic Algorithms. Evolutionary Computation Journal, 14:2, pp 157-182, MIT Press] in Genetic Algorithms and has been linked to the concept of Optimal Mutation Rate. In this paper, the author expands previous works with a study of Error Thresholds near 1 (i.e. mutation probabilities of approx. 0.95), in the context of binary encoded chromosomes. Comparative empirical tests are performed, and the author draws conclusions in the context of population consensus sequences, population size, mutation rates and error thresholds.