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Frame Sizing and Topological Optimization Using a Modified Particle Swarm Algorithm

机译:使用改进的粒子群算法的帧大小调整和拓扑优化

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as a comparatively new developed stochastic method particle swarm optimization (PSO), it is widely applied to various kinds of optimization problems especially of nonlinear, non-differentiable or non-convex types. In this paper, a modified guaranteed converged particle swarm algorithm (MGCPSO) is proposed in this paper, which is inspired by guaranteed converged particle swarm algorithm (GCPSO) proposed by von den Bergh. In this paper, the sizing and topological optimization problems of steel framed structures subjected to stress and displacement constraints are selected to illustrate the performance of the presented optimization algorithm. The obtained competitive results show that the MGCPSO exhibit good performance due to improved global searching ability.
机译:作为一种比较新开发的随机方法粒子群算法(PSO),它已广泛应用于各种优化问题,尤其是非线性,不可微或非凸类型的优化问题。本文提出了一种改进的保证收敛的粒子群算法(MGCPSO),该算法受冯·登·伯格(von den Bergh)提出的保证收敛的粒子群算法(GCPSO)的启发。本文选择了受应力和位移约束的钢框架结构的尺寸和拓扑优化问题,以说明所提出的优化算法的性能。获得的竞争结果表明,由于提高了全局搜索能力,MGCPSO表现出良好的性能。

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