Application of finite element inverse model based on improved particle swarm optimization and mixed penalty function

JIA Shan-po; WU Guo-jun; CHEN Wei-zhong

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Application of finite element inverse model based on improved particle swarm optimization and mixed penalty function

更新时间：2026-06-25

- Application of finite element inverse model based on improved particle swarm optimization and mixed penalty function
- Vol. 32, Issue S2, (2011)
- 作者机构：
  
  1. 长江大学城市建设学院,湖北,荆州,434023
  2. 山东大学岩土与结构工程研究中心,济南,250061
  3. 中国科学院武汉岩土力学研究所岩土力学与工程国家重点实验室,武汉,430071
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU452
- Online First：26 August 2011，
  
  Published：2011
- 稿件说明：
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JIA Shan-po, WU Guo-jun, CHEN Wei-zhong. Application of finite element inverse model based on improved particle swarm optimization and mixed penalty function[J]. 2011, 32(S2).
DOI：

JIA Shan-po, WU Guo-jun, CHEN Wei-zhong. Application of finite element inverse model based on improved particle swarm optimization and mixed penalty function[J]. 2011, 32(S2). DOI：

摘要

岩土工程优化反分析是一个典型的复杂非线性函数优化问题，采用全局优化算法是解决这个问题的理想途径。针对常规反演方法应用于岩土工程参数反演时搜索效率低的缺点，结合粒子群算法和遗传算法的特点，充分考虑二者的互补性，提出一种效率较高的全局优化算法，以测点的实测值与计算值建立一种新的评价函数，将多目标优化问题转化为单目标优化问题，用混合罚函数法将约束问题变为无约束问题，构建了一种新的目标函数，将有限元程序ABAQUS作为一个模块嵌入到优化算法程序中，编制了有限元优化反演分析程序。并给出了应用实例验证了该法的有效性和实用性，是一种可行的参数反演方法，可应用于实际工程中复杂岩土介质初始应力场反演、渗流场以及位移反分析

Abstract

The inverse analysis in geotechnical engineering is a typical complicated nonlinear function optimization problem. To solve this problem

the global optimization algorithm is a very good method. In order to offset the disadvantages of low searching efficiency using traditional methods of back analysis

the particle swarm optimization and genetic algorithm are hybridized to construct a global optimization algorithm according to their compatibility and algorithm complementary. A new evaluation function method is established which unites multiobjective function to single objective function according to the actually measures and corresponding calculated results. The mixed penalty function method is adopted to transform constraint condition to unconfined condition and a new objective function is presented. Based on the improved particle swarm optimization

the program of back analysis is coded

in which ABAQUS is embedded as a module in the optimization algorithm. Through a tunnel model as an example

the proposed inverse program is verified; and the results show that this method is a very good inverse analysis method and its efficiency is very good. So the proposed method is a feasible method for back analysis of stress

seepage and displacement in geotechnical engineering.

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