Abstract

. It is sometimes claimed that genetic algorithms using diploid representations will be more suitable for problems in which the environment changes from time to time, as the additional information stored in the double chromosome will ensure diversity, which in turn allows the system to respond more quickly and robustly to a change in the fitness function. We have tested various diploid algorithms, with and without mechanisms for dominance change, on non-stationary problems, and conclude that some form of dominance change is essential, as a diploid encoding is not enough in itself to allow flexible response to change. Moreover, a haploid method which randomly mutates chromosomes whose fitness has fallen sharply also performs well on these problems. 1 Introduction Genetic algorithms (GAs) are often used to tackle problems which are stationary, in that the success criteria embodied in the fitness function do not change in the course of the computation. In a non-stationary prob...

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