Evolutionary Computation with User’s Preference for Solving Fuzzy Fitness Forecasting Problems

Interactive Evolutionary Computation (IEC) is a kind of human–machine interaction calculation method derived from evolutionary computation. The main problem of interactive evolutionary computation is that fitness noise can make evolution direction to deviate from user’s preferences because user’s evaluation has cognitive fluctuations and fatigue. To improve these deficiencies, this paper recommends a fuzzy fitness prediction method based on fuzzy gray model FGM (1,1) with a precise number fitness. First of all, the relationship between fitness noise intensity and the fitness function is proposed. Then, it suggests a linear programming of fuzzy fitness set width under the restriction of minimum noise intensity, which can calculate the fuzzy fitness prediction parameters. Finally, the fuzzy gray model forecasts the fuzzy fitness. The proposed method uses new computation of individual’s dominance relation and crowding distance to realize NSGA–II. The experimental results verify that this method has advantages in improving optimization quality, alleviating user’s fatigue and improving efficiency in exploration.

The alternative fitness sets which preserve allele trajectories: a general treatment.

A general solution is presented of the problem of specifying all alternative, generally frequency-dependent, (absolute) fitness sets which give rise to the same allele frequency changes and population dynamics as a given fitness set. The one- and two-locus cases are analyzed in detail and the method is then extended to the n-locus case. It is shown that if biological constraints can be used to specify the mean fitness of the population and the relative fitnesses of the heterozygotes, then the allele frequency trajectories determine a unique fitness set.

Adaptation to environmental heterogeneity in populations of Drosophila melanogaster

SummaryFor 29 generations, populations of Drosophila melanogaster were offered one favourable (standard) and one suboptimal (salt-supplemented) medium, either singly or simultaneously. Egg-to-adult viability, fecundity and choice of oviposition medium were measured at regular intervals on both resources up to 17 generations after initiation of the salt treatment. Except for a decrease in viability on salt medium in the single-resource populations (SRPs) maintained on the optimal medium, these fitness components remained unchanged. Estimation of a more inclusive measure of fitness, productivity, obtained at generations 27–29, revealed that: (1) the SRPs maintained on salt medium were more adapted to salt medium; (2) the mixed-resource populations (MRPs) were intermediate in their adaptation to salt medium between either type of single-resource population. These results support Levins' model of optimal strategy for populations living in a coarse-grained environment when the fitness set is convex. Family selection for increased and decreased resistance to salt in the medium, carried out for the viability component at generations nine and 19, showed that: (1) genetic variation with respect to this component was present in all populations; (2) the SRPs maintained on salt medium had responded to the salt treatment by eliminating sensitive genotypes; (3) in the first selection experiment, the MRPs had a greater amount of additive genetic variance with respect to viability than either type of SRP; in the second experiment, this difference was not significant, but it was in the predicted direction. The latter finding provides some evidence in favour of the hypothesis repeatedly presented in the literature that environmental heterogeneity could promote the maintenance of genetic variability in populations.