A Comparative Study of Evolutionary Algorithm and Swarm Algorithm for Airfoil Shape Optimization Problems

Abstract

Shape optimization of airfoils involves highly expensive, nonlinear objective(s) and constraint functions. Zero order, stochastic methods are often used to handle such problems. In this paper, we report the performance of two such methods; Evolutionary Algorithm (EA) and the Swarm Algorithm (SWARM) on five airfoil shape optimization problems. Both the EA and the SWARM algorithm used here are variants of their original form suited to handle multiple objectives and multiple constraints without aggregation. Their original form were meant to solve unconstrained single objective problems. The present studies indicate that the EA marginally outperforms SWARM for single objective problems in terms of the computational efficiency while for the multiple objective problems, the SWARM exhibits a better overall performance in locating the Pareto front. Both methods exhibit fast convergence capabilities and provide the designer the flexibility of cost function choices that is necessary to solve various forms of the shape optimization problems. © 2003 by T. Ray and H.M. Tsai.