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Structural analysis of Pareto-optimal solution sets for multi-objective optimization: An application to outer window design problems using Multiple Objective Genetic Algorithms

机译:多目标优化的帕累托最优解集的结构分析:使用多目标遗传算法的外窗设计问题的应用

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摘要

In single-objective optimization problems, with only one optimal design objective, the absolute optimal solution to maximize/minimize the objective function can be determined. However, in most real design problems, the optimization problems are multi-objective, where two or more independent design objectives must be optimized simultaneously, and no single absolute optimal solution necessarily exists. In these cases, it is helpful for designers to recognize the range of alternative solutions that exist in Pareto-optimal sets and choose an acceptable solution from among them. In this paper, the authors carried out multi-objective optimization using Multiple Objective Genetic Algorithms through a real case study involved in indoor environmental design - the design of outer windows. Then the authors analyzed structure of Pareto-optimal solution sets. Here we present the analysis process as well as the case study details, and show how the method proposed here is effective at finding an acceptable solution for multi-objective optimization problems.
机译:在只有一个最优设计目标的单目标优化问题中,可以确定最大化/最小化目标函数的绝对最优解。但是,在大多数实际设计问题中,优化问题是多目标的,其中必须同时优化两个或多个独立的设计目标,并且不必存在单个绝对最优解。在这些情况下,有助于设计人员识别Pareto最优集合中存在的替代解决方案的范围,并从中选择可接受的解决方案。在本文中,作者通过涉及室内环境设计(外窗设计)的实际案例研究,使用多目标遗传算法进行了多目标优化。然后作者分析了帕累托最优解集的结构。在这里,我们介绍了分析过程以及案例研究的详细信息,并说明了本文提出的方法如何有效地为多目标优化问题找到可接受的解决方案。

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