Efficient global optimization with co-evolutionary strategy for asymmetric minimax problem in robust design

Minimax optimization (MMO), which aims at pursuing the solutions with the best performances in the worst case, is widely used in the robust design. However, there are still fundamental limitations for MMO to converge to the optimum when solving asymmetric problems. Moreover, when MMO is employed in robust design where the objective function is evaluated through costly simulations, the efficiency of the optimization becomes crucial. To address these issues, in this paper, A novel efficient global optimization algorithm based on co-evolutionary strategy is proposed to solve the asymmetry MMO problem with satisfactory efficiency. Furthermore, the new algorithm is tested on eight analytical benchmark problems and compared with the state-of-the-art methods. Lastly, the methodology has been successfully applied to the robust design of a practical engineering product.