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Design and optimization of form and facade of an office building using the genetic algorithm

机译:使用遗传算法设计和优化办公楼的形式和外观

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One of the most important sustainable building design goals is energy performance throughout the life cycle of the building. In this article, the optimization of an office building facade has been performed using a genetic algorithm with the sustainability approach. Multi-objective optimization using an The Strength Pareto Evolutionary Algorithm (SPEA-2) algorithm gives the amount of solar radiation received by the building's envelope and useful interior space and shape coefficient of the design based on the cooling load, heating load, and natural light supplied to the building. In order to achieve the project objectives, parametric modeling was used with Grasshopper software and environmental analysis tools, Ladybug and Honeybee. In both optimization steps, the optimal solution was selected on the Pareto front and, according to the designer, the decision was made between the optimal results. Optimization has led to an improvement in usable space, reduced thermal load, and improved natural light in the building. Using Pareto front, genetic algorithms and parametric modeling have a significant role in developing a sustainable design. The process and results of this research help architects and designers to find a more sustainable design and facade for the building.
机译:最重要的可持续建筑设计目标之一是整个建筑物生命周期的能源表现。在本文中,使用具有可持续性方法的遗传算法进行了办公楼外观的优化。使用强度帕累托进化算法(SPEA-2)算法的多目标优化为基于冷却负荷,加热负荷和自然光而提供的建筑物包络和有用的内部空间和具有设计系数的太阳辐射量。提供给建筑物。为了实现项目目标,参数建模与蚱蜢软件和环境分析工具,瓢虫和蜜蜂一起使用。在两个优化步骤中,在Pareto前面选择最佳解决方案,并且根据设计者,在最佳结果之间进行决定。优化导致可用空间,减少热负荷和建筑物中的自然光的改善。使用帕累托前部,遗传算法和参数建模在开发可持续设计方面具有重要作用。本研究的过程和结果有助于建筑师和设计师找到建筑物更可持续的设计和门面。

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