Center Based Genetic Algorithm and its application to the stiffness equivalence of the aircraft wing

In this paper, a kind of Center Based Genetic Algorithm (CBGA) is proposed to overcome the premature convergence and to solve the stiffness equivalence problem. With the information of population center, central chaotic mutation and space shrinking strategy are designed to guide the evolutionary searching process. Meanwhile, the rank value based roulette selection and a new Cauchy preferential crossover operator are collaboratively used with the mutation operators in the CBGA. To avoid the loss of the best solution, the elitist strategy is employed as well. In addition, local search is embedded in the CBGA after the main evolutionary search process to enhance the exploitation ability by further improving the elite solution. Numerical simulation and comparison based on a set of benchmark functions show that, the proposed CBGA is superior to the hybrid genetic algorithm from the literature in terms of searching efficiency, solution quality, robustness and success ratio. Finally, CBGA is applied to successfully solve the stiffness equivalence problem of the small-aspect-ratio aircraft wing to tapered beam.