基于多基因辅助 NSGA-II 的建筑节能设计多目标优化方法

Q2 Energy Energy Informatics Pub Date : 2024-09-27 DOI:10.1186/s42162-024-00394-4
Zhiwei Zhang
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引用次数: 0

摘要

本研究开发了一种新型多代理增强 NSGA-II 架构,专门用于高效处理建筑节能设计中的高维多目标优化挑战。本文摒弃了共享 Q 方法,采用了一种新颖的拥挤评价和比较机制,以确保在保持种群多样性的同时全面覆盖准帕雷托前沿。集成快速非支配排序后,算法的计算压力得以有效降低。精英策略的融入进一步扩大了解空间,避免了最优解的遗漏,从而提高了算法的运行效率和稳定性。经过对 50 个实际建筑实例的深入分析,结果表明,与传统的 NSGA-II 方法相比,我们的方法优化了帕累托解的质量和多样性,平均提高幅度分别为 12% 和 15%,同时显著缩短了计算时间,为建筑节能设计实践带来了一条创新、高效的优化路径。
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Multi-objective optimization method for building energy-efficient design based on multi-agent-assisted NSGA-II

This study develops a novel multi-agent augmented NSGA-II architecture specifically designed to efficiently handle high-dimensional multi-objective optimization challenges in building energy-efficient design. In this paper, the share Q method is abandoned, and a novel crowding evaluation and comparison mechanism is adopted to ensure comprehensive coverage of the quasi-Pareto frontier while maintaining the diversity of the population. After integrating fast non-dominated sorting, the computational pressure of the algorithm can be effectively reduced. The integration of elite strategies further expands the solution space and prevents the omission of optimal solutions, thereby improving the operating efficiency and stability of the algorithm. After an in-depth analysis of 50 actual building examples, the results show that compared with the conventional NSGA-II method, our method optimizes the quality and diversity of Pareto solutions, with an average improvement of 12% and 15% respectively, while significantly shortening the calculation time, bringing an innovative and efficient optimization path to the energy-saving practice of building design.

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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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