.png){kind=icon}
返回
Optimization of retaining wall design using evolutionary algorithms
.png){kind=icon}
PRE
AI
DOI：10.1007/s00158-016-1521-3.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper explores the performance of three evolutionary optimization methods, differential evolution (DE), evolutionary strategy (ES) and biogeography based optimization algorithm (BBO), for nonlinear constrained optimum design of a cantilever retaining wall. These algorithms are based on biological contests for survival and reproduction. The retaining wall optimization problem consists of two criteria, geotechnical stability and structural strength, while the final design minimizes an objective function. The objective function is defined in terms of both cost and weight. Constraints are applied using the penalty function method. The efficiency of the proposed method is examined by means of two numerical retaining wall design examples, one with a base shear key and one without a base shear key. The final designs are compared to the ones determined by genetic algorithms as classical metaheuristic optimization methods. The design results and convergence rate of the BBO algorithm show a significantly better performance than the other algorithms in both design cases.
Keyword:
Metaheuristic algorithms
Retaining wall
Evolutionary algorithms
Differential evolution
Evolutionary strategy
Biogeography based optimization algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
4.9K
被引数:
1.7W
机构
引用论文
Imperialistic Competitive Algorithm: A metaheuristic algorithm for locating the critical slip surface in 2-Dimensional soil slopes帝国竞争算法: 一种用于在二维土坡中定位临界滑动面的元启发式算法.png)
GEOSCIENCE FRONTIERS
OAAI
GEOSCIENCE FRONTIERSIF8.9
OAAI分享收藏分享收藏Measurement and age assignment of intact rock strength in the Krkonose Mountains, Czech Republic
PREAI
分享收藏分享收藏
查看更多内容