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首页> 外文会议>International PhD Symposium in Civil Engineering vol.2; 20040616-19; Delft(NL) >Genetic algorithms for structural optimization of large-span roof trusses
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Genetic algorithms for structural optimization of large-span roof trusses

机译：大跨度屋架结构优化的遗传算法

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摘要

This paper discusses a new research effort that focuses on genetic algorithms as a tool for optimizing large-span roof trusses. The objectives to be minimized are truss weight, deflection, and fabrication cost. Decision variables include overall truss topology, joint geometry, and member sizing. A multi-objective genetic algorithm using an implicit redundant representation will be employed. Additionally, this research will incorporate user-feedback, in the form of penalty constraints, to guide the selection of aesthetically appealing design alternatives. In recent years, traditional optimization methods have been supplemented by heuristic algorithms that strive to blend mathematical models with expert knowledge. One such emerging method is the genetic algorithm, an optimization technique with roots in the theory of evolution and survival of the fittest. This paper details a new research effort to use genetic algorithms (GAs) in the design of large-span roof trusses. The long-term research goal is to create a program for generating more efficient designs while reducing project costs. This paper presents background material on GAs, a description of the problem, and the proposed research methodology.
机译：本文讨论了一项新的研究工作，该工作侧重于遗传算法，作为优化大跨度屋架的工具。要最小化的目标是桁架重量，挠度和制造成本。决策变量包括整体桁架拓扑，接头几何形状和成员尺寸。将采用使用隐式冗余表示的多目标遗传算法。此外，这项研究还将结合惩罚约束形式的用户反馈，以指导选择美观的设计替代方案。近年来，传统的优化方法得到了启发式算法的补充，该算法试图将数学模型与专家知识相融合。一种这样的新兴方法是遗传算法，这是一种基于优胜劣汰的进化理论的优化技术。本文详细介绍了在大跨度屋顶桁架设计中使用遗传算法（GA）的新研究成果。长期的研究目标是创建一个程序，以生成更有效的设计，同时降低项目成本。本文介绍了遗传算法的背景材料，问题的描述以及拟议的研究方法。

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