分布式协同进化MDO算法及其在导弹设计中应用

 针对现有基于梯度的多学科设计优化 (MDO)算法不适用于具有离散和整数设计变量、设计空间非凸或不连通的多学科设计优化问题,以及倾向于收敛到接近初始点的局部最优点的缺点,为充分发挥进化算法的优越性,根据协同进化与 MDO在本质上的相似性,采用分布式协同进化机制进行 MDO算法研究。提出了分布式协同进化 MDO算法,并将该算法应用于导弹的气动 /发动机 /控制一体化优化设计。

MULTIDISCIPLINARY DESIGN OPTIMIZATION BASED ON DISTRIBUTEDCOEVOLUTION-ALGORITHM AND APPLICATION IN MISSILE DESIGN

Gradient\|based multidisciplinary design optimization (MDO) methods cannot be used directly to problems with discrete and integer design variables or with disjointed design space, and they have a propensity to converge to a relative optimum closest to the starting point. This paper introduces coevolutionary algorithms to multidisciplinary design optimization based on their substantial similarity, to sufficiently employ the merit of evolutionary algorithms in MDO. A distributed coevolutionary multidisciplinary design optimization algorithm is proposed. Each discipline conducts optimization using an independent distributed evolutionary algorithm. The distributed coevolution mechanism is used to coordinate disciplinary optimizations. The algorithm is applied to missile aerodynamic/engine/control multidisciplinary design optimization, and the result shows that the algorithm is promising in design optimization of coupled systems.