基于粒子群算法的平面刚架及组合结构的优化

桁架结构受力简单,内力只有轴力,刚架结构的受力、内力情况则相对要复杂得多,故传统平面结构优化的研究多是对桁架结构的研究,针对刚架结构或刚架与桁架的组合结构研究甚少.然而,现实工程中的结构多是刚架或组合结构,仅仅对桁架结构进行优化研究远远不能满足现实工程的需要.粒子群优化算法(PSO)是近些年发展起来的一种基于群智能的演化运算技术,概念简单、易于实现,且具有良好的智能背景.本文基于粒子群优化算法对平面刚架及平面组合结构的有应力约束和位移约束的尺寸优化问题进行了研究,并将所得优化结果与改进的可行域算法(MMFD)、序列线性算法(SLP)、序列二次规划(SQP)等传统优化算法的结果进行比较.结果表明粒子群优化算法具有良好的全局收敛性与稳定性,能够更好地解决平面刚架及平面组合结构的优化问题.

The Optimization of Plane Frame and Composite Structures Based on Particle Swarm Optimization Algorithm

Compared with truss structures whose internal force only include axial force , and the frame has much more complicated loadings and internal forces .Therefore , most of the study of the plane structural optimization is on truss structures .However , in engineering , more and more application of frames and composite structures call for the study of optimization on them .Particle swarm optimization algorithm （ PSO） is a kind of evolutionary computation technique based on swarm intelligence .It is simple, easy to implement and good intelligence background .The paper studied the size optimization of the frames and the composite structures based on PSO and compared the results of PSO with those by improved feasible region of algorithm （ MMFD） , sequence linear programming （ SLP） and sequential quadratic programming （ SQP ） .The comparison shows that PSO has better global convergence and stability in solving the optimization problems of frames and composite structures .