A deterministic annular crossover genetic algorithm optimisation for the unit commitment problem

► In genetic algorithms, selection based on the quality produce premature convergence. ► Crossover is sensitive to the gene position when the representation of the chromosome, is linear. ► The ends of this type of chromosome have very low probability of changing by mutation. ► A genetic algorithm is applied to the unit commitment problem using a deterministic selection operator and an annular crossover.