基于QPSO算法的钢管混凝土构件的优化

Optimization of Concrete-filled Steel Tubular Members Based on QPSO Algorithm

钢管混凝土具有承载力高,韧性和塑性好以及施工方便等的优点,近些年在高层建筑中应用广泛。本文采用量子粒子群算法,将其应用到钢管混凝土结构构件的设计优化中,以满足梁柱的各项力学指标为约束条件,经济指标(最小)为目标函数,并与标准PSO算法和改进的GA算法的优化结果进行比较,结果表明在承载力符合设计要求的前提下,量子粒子群算法求得了更小的目标函数值,达到了梁柱构件造价最低的目的。

Concrete-filled steel tubular(CFST)has the advantages of high bearing capacity,good toughness and plasticity,and convenient construction.It has been widely used in high-rise buildings in recent years.In this paper,quantum particle swarm optimization(QPSO)algorithm is used to optimize the design of CFST.Taking the mechanical index of beam and pillars as the constraint condition and the economic index(minimum)as the objective function,and comparing with the optimization results of PSO algorithm and the improved GA algorithm,the results show that the bearing capacity meets the design requirements.QPSO algorithm has obtained a smaller objective function value and achieved the lowest cost of beam and pillars component.