A hybrid crossover operator for structural optimisation based on commonality in genetic search
A new design framework for crossover operator is proposed based on the commonality concept In the reproduction process the resulting hybrid crossover operator includes a local search scheme aiming to improve the genetic characteristics of the offspring. Commonality suggests that search should be driven in the neighbourhood of parents, and local optimisers can drive this search. The ranking of the offspring candidates is based on a local fitness function using approximations and appropriated heuristics linked to the structural optimisation problem. The goal of this approach is to identify and preserve the common schema of the two parents responsible for their high-observed fitness. The proposed hybrid crossover operator is embedded into a genetic algorithm supported by an elitist strategy and its performance is compared with the parametrised uniform crossover.
genetic algorithms structural optimization