SOLUTION ANALYSIS IN MULTI-OBJECTIVE OPTIMIZATION
SOLUTION ANALYSIS IN MULTI-OBJECTIVE OPTIMIZATION
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发表时间：
2012
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通讯作者：
A. Brownlee;J. Wright
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作者：
A. Brownlee;J. Wright
近年来，人们越来越多地使用进化算法来优化多目标建筑设计问题。其目的是在相互冲突的设计目标（如资本成本和运营能源使用）之间找到帕累托最优权衡。分析结果解决方案集可能很困难，特别是在需要考虑大量（可能是数百个）设计变量的情况下。本文回顾了现有的分析帕累托前沿的方法。然后介绍了一种新的方法来分析权衡，基于目标的简单排序，以及目标和问题变量之间的相关性。这允许对设计目标和变量之间的权衡进行分析。通过示例构建演示了该方法，涵盖了变量和目标之间可能存在的不同关系。
Recent years have seen a growth in the use of evolutionary algorithms to optimize multi-objective building design problems. The aim is to find the Pareto optimal trade-off between conflicting design objectives such as capital cost and operational energy use. Analysis of the resulting set of solutions can be difficult, particularly where there are a large number (possibly hundreds) of design variables to consider. This paper reviews existing approaches to analysis of the Pareto front. It then introduces new approach to the analysis of the trade-off, based on a simple rank- ordering of the objectives, together with the correlation between objectives and problem variables. This allows analysis of the trade-off between the design objectives and variables. The approach is demonstrated for an example building, covering the different relationships that can exist between variables and the objectives.