Research on application of evolutionary strategy and its improved algorithm to optimization design of foundation pit supporting

HOU Gong-yu; MI Shang-yin; YANG Chun-feng

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Research on application of evolutionary strategy and its improved algorithm to optimization design of foundation pit supporting

更新时间：2026-06-25

- Research on application of evolutionary strategy and its improved algorithm to optimization design of foundation pit supporting
- Vol. 29, Issue 5, (2008)
- 作者机构：
  
  1. 中国矿业大学,北京,100083
  2. 中航勘察设计研究院,北京,100089
  3. 中国京冶建设工程承包公司,北京,100088
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU473.2
- Online First：24 July 2013，
  
  Published：2008
- 稿件说明：
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HOU Gong-yu, MI Shang-yin, YANG Chun-feng. Research on application of evolutionary strategy and its improved algorithm to optimization design of foundation pit supporting[J]. 2008, 29(5).
DOI：

HOU Gong-yu, MI Shang-yin, YANG Chun-feng. Research on application of evolutionary strategy and its improved algorithm to optimization design of foundation pit supporting[J]. 2008, 29(5). DOI：

摘要

进化策略是一种新的求解全局最优问题的方法，应用该方法对深基坑支护结构进行了优化设计的初步研究。针对进化策略在处理非线性函数的优化问题及高维优化问题时在收敛速度和收敛性方面存在的不足，将禁止搜索与有向搜索相结合，提出了一种快速进化策略算法，有效地克服了传统进化策略的缺点。工程实例分析研究表明，进化策略不受设计空间的可微性、连续性等限制，特别适合于求解支护工程这类具有离散设计变量和非确定性因素的工程设计问题；改进的进化策略具有更好的收敛性，有极强的避免局部极值的全局优化能力。

Abstract

Evolutionary strategies is a new method when it comes to solve the optimal solution of the global optimization issues; at the same time

the study of optimization design in the pit supportings by using the theories and methods of evolutionary strategies is carried out. Considering the optimization design’s disadvantages in convergence and convergence speed when it deals with optimization issues of nonlinear function and high-dimension optimization

a sort of faster evolutionary strategy is presented by combining the tabu search(TB) with the beam search which can effectively overcome the downbacks mentioned upon. Taking the studies and analysis of some cases of construction as background

which indicates that evolutionary strategies are not confined by the differentiability

continuity of design space and so on; but especially fit for calculating the issues of the supporting projects which relating to discrete design variables and uncertain factors. The new improved evolutionary strategy presented has a better convergence as well as the capabilities of the global optimization which avoids local optimum solutions effectively.

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