粒子群算法在工程优化设计中的应用

Application of Particle Swarm Optimization in the Engineering Optimization Design

将粒子群算法与惩罚函数法相结合,建构一种离散粒子群算法,解决工程上非线性约束离散变量优化设计问题。为实现离散变量与连续变量的转化,构造了相应的扩张函数,提出惩罚因子的确定策略。通过容器设计算例验证,粒子群算法方法优于文献所列方法。应用粒子群算法、惩罚函数法及所提出的策略对波纹管工程实例进行优化设计,其单位重量下整体波纹管的补偿量比在用产品提高了79.96%,与理论解接近,进一步证明了离散粒子群算法及策略在处理工程非线性约束离散优化设计问题时的有效性,其为工程上类似优化设计提供借鉴。

A discrete partcle swarm optimization （PSO） is proposed to solve the problem of nonlinear constraints discrete optimization design in engineering, in which the penalty function is employed to transform discrete design variables to continuous design variables. An augment function is constructed and a new scheme of penalty parameter is proposed. The validity of proposed approach is examined by the famous benchmark-vessel design, the comparison results show that the proposed discrete particle swarm optimization is superior to the other algorithms from literatures and has better convergence performances. The proposed approach is applied further in the optimal design of bellows, the global optimums are obtained, the objective function value of maximum bellow s movement per weight unit is 79.9% improved than that of products in-service and it nears to theoretical solution. Therefore, the validity of the proposed approach is been examined, and the proposed discrete particle swarm optimization and scheme can be used to solve the problem of nonlinear constraints discrete optimization design in engineering.