EXAMPLES OF GENETIC ALGORITHMS USAGE IN GEOMETRY AND ALGORITHMIC DESIGN

Michał Nessel, Szymon Filipowski
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Abstract

In this paper, the authors test genetic algorithms as geometric and design issues’ solvers to explain and explore the possibilities of this computing technique in design and research. The tests and explanations are based on three classical geometry problems of the Ancient Greece and on a pattern distribution algorithm, created by the authors and inspired by the definition of Lebesgue covering dimension. The basic tools for research are: Rhinoceros, the Grasshopper plug-in and the Galapagos tool. The tests prove that, as a result based on computing techniques, genetic algorithms can be used to find solutions without the implementation of analytic methods. This advantage of evolutionary computing can be very useful in case of complex issues, where implementation of analytic methods reveals itself difficult or even impossible.
遗传算法在几何和算法设计中的应用实例
在本文中,作者测试了遗传算法作为几何和设计问题的解决方案,以解释和探索这种计算技术在设计和研究中的可能性。测试和解释是基于古希腊的三个经典几何问题和模式分布算法,由作者创建,并受到勒贝格覆盖维的定义的启发。用于研究的基本工具是:Rhinoceros, Grasshopper插件和Galapagos工具。实验证明,基于计算技术的遗传算法可以在不执行解析方法的情况下找到解。进化计算的这一优势在复杂问题的情况下非常有用,在这种情况下,分析方法的实现是困难的,甚至是不可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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