Particle Swarm Assisted Genetic Algorithm for the Optimal Design of Flexbeam Sections
Manoj Kumar Dhadwal , Kyu Baek Lim, Sung Nam Jung and Tae Joo Kim
International Journal of Aeronautical and Space Sicences, vol. 14, no. 4, pp.341-349, 2013
Abstract : This paper considers the optimum design of flexbeam cross-sections for a full-scale bearingless helicopter rotor, using an
efficient hybrid optimization algorithm based on particle swarm optimization, and an improved genetic algorithm, with an
effective constraint handling scheme for constrained nonlinear optimization. The basic operators of the genetic algorithm,
of crossover and mutation, are revisited, and a new rank-based multi-parent crossover operator is utilized. The rank-based
crossover operator simultaneously enhances both the local, and the global exploration. The benchmark results demonstrate
remarkable improvements, in terms of efficiency and robustness, as compared to other state-of-the-art algorithms. The
developed algorithm is adopted for two baseline flexbeam section designs, and optimum cross-section configurations are
obtained with less function evaluations, and less computation time.
Keyword : Beam Section Optimization, Real-Coded Genetic Algorithm, Particle Swarm Optimization, Rank-based Multi- |