Evaluation of Metaheuristic Algorithms for the Improvement of Sustainability in the Construction Area

Lluís Aunós i Chicón, Pau Fonseca i Casas
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Abstract

NECADA infrastructure supports the execution of a simulation model of buildings or urban areas, taking care of environmental directives and international standards in the design process. The aim of this simulation model is to optimize the entire life cycle of the system from the point of view of sustainability (environmental, social and economic impacts), taking care of the comfort and climate change to achieve a Nearly Zero Energy Building. Due to the huge amount of factors to be considered, the number of scenarios to be simulated is huge, hence the use of optimization and specifically heuristics, is needed to get an answer in a reasonable time. This project aims to analyze the accuracy of two of the most used metaheuristics in this area. To do so we base our analysis in an extensive dataset obtained from a brute force execution, which represents a typical dataset for this kind of problem.
建筑区域可持续性改进的元启发式算法评价
NECADA基础设施支持建筑物或城市地区的模拟模型的执行,在设计过程中照顾环境指令和国际标准。该模拟模型的目的是从可持续性(环境、社会和经济影响)的角度优化系统的整个生命周期,同时兼顾舒适性和气候变化,以实现接近零能耗的建筑。由于需要考虑的因素非常多,需要模拟的场景数量也非常多,因此需要使用优化方法,特别是启发式方法,以便在合理的时间内得到答案。本项目旨在分析这一领域最常用的两种元启发式的准确性。为了做到这一点,我们基于从暴力执行中获得的广泛数据集进行分析,该数据集代表了此类问题的典型数据集。
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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