基于HPSO算法的CFG桩复合地基优化设计

Optimization Design Method of Cement Fly-ash Gravel Pile Composite Foundation Based on HPSO Algorithm

复合粒子群优化(HPSO)算法是一类随机全局优化技术,具有搜索能力强、收敛速度快、搜索精度高的优点。针对水泥粉煤灰碎石桩(CFG桩)复合地基设计中的优化问题,利用FLAC软件自带的fish语言实现了HPSO算法对CFG桩复合地基多个设计参数的优化辨识。该方法从设计参数的随机值出发,以CFG桩施工时所需混合料方量作为目标函数来评价参数的品质,利用HPSO算法规则实现设计参数的进化,搜索出全局最优的设计参数值,从而实现了CFG桩复合地基设计参数的自适应辨识。利用该方法对某工程CFG桩复合地基进行了多参数优化设计。结果表明,HPSO算法用于CFG桩复合地基优化设计是有效的,能在满足设计及相关规范的前提下有效降低工程成本,提高经济效益。

Hybrid Particle swarm optimization （HPSO） algorithm is a stochastic global optimization technique with many advantages, such as quick convergence, simple regulation and easy implementation. In order to determine the multi-pa- rameters of cement fly-ash gravel （CFG） pile composite foundation, in this article, a new method is presented using HPSO al- gorithm and fish language, which was contained in FLAC. At first, the stochastic values of parameters are initialized and the quantity of CFG was regarded as fitness function to evaluate quality of the parameters. Then the parameters are updated contin- ually using HPSO until the optimal parameters are found. Thus parameters of CFG pile composite foundation are identified a- daptively during computation. This method was used in the design of CFG pile composite foundation in a project, and the re- sults show that HPSO algorithm is effective in designing of cement fly-ash gravel pile composite foundation, which can reduce engineering cost and increase economic efficiency effectively.