Optimization of building fenestration and shading for climate-based daylight performance using the coupled genetic algorithm and simulated annealing optimization methods
Optimization of building fenestration and shading for climate-based daylight performance using the coupled genetic algorithm and simulated annealing optimization methods
复制标题
使用耦合遗传算法和模拟退火优化方法优化建筑开窗和遮阳，以实现基于气候的日光性能
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
F. Kheiri
中科院分区：
文献类型：
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作者：
F. Kheiri
由于开窗特性对采光性能的复杂性和非线性影响，各种元启发式优化方法已应用于高性能玻璃窗和遮阳系统设计。然而，由于优化方法的随机性和配置，不同的优化方法得到的最优解可能会有所不同。研究了混合模拟退火遗传算法（GA）在可靠性、一致性和鲁棒性方面的改进，考虑了SA中不同的冷却策略，包括初始温度和每个温度下的状态转换，从而控制了SA搜索的全面性和收敛速度。通过对不同优化方法中最优情况下目标函数值的均值和方差的分析，发现混合GA/SA与GA在温度较高的情况下存在显著差异，混合算法的性能优于GA。
Various metaheuristic optimization methods have been applied in high-performance glazing and shading system design due to the complexity and nonlinear impact of the fenestration characteristics on the daylighting performance. However, the optimal solutions found by different optimization methods may vary because of the stochastic nature and the configurations of the optimization methods. This paper studied the improvements in the reliability, consistency and robustness of the genetic algorithm (GA) using hybridization with simulated annealing (SA) considering different cooling strategies in the SA, including the initial temperature and state transitions for each temperature, which controls the comprehensiveness and the convergence acceleration of the search by SA. Analysis of the reliability, consistency and robustness of the optimization methods based on the mean values and the variances of the objective function values of the best cases found in different methods revealed that there is a significant difference between the hybrid GA/SA with higher temperature and GA, where hybrid algorithm performed better than the GA.
影响因子：
2.5
作者：
J. Wright;A. Brownlee;M. Mourshed;Mengchao Wang
通讯作者：
J. Wright;A. Brownlee;M. Mourshed;Mengchao Wang