A Novel Method for Calculating the Parametric Hypervolume Indicator

Jonathan M. Weaver-Rosen, R. Malak
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Abstract

This paper presents a new methodology for calculating the hypervolume indicator (HVI)for multi-objective and parametric data. Existing multi-objective HVI calculation techniques cannot be directly used for parametric data because designers do not have preferences for parameters like they do for objectives. The novel method presented herein allows for the consideration of both objectives and parameters through the newly introduced hypercone heuristic (HCH). This heuristic relaxes the strict rules of parametric Pareto dominance for a more practical dominance assessment when comparing designs of differing parameter values without violating Pareto dominance rules. A parametric HVI (pHVI) enhances a design engineer’s toolkit by enabling both online and offline evaluation of parametric optimization results. The pHVI measure allows designers to compare solution sets, detect optimization convergence, and to better inform optimization procedures in a parametric context. Results show that the HCH-based pHVI yields a similar quality measure to the existing technique based on a support vector domain description (SVDD) in a fraction of the computational time. Furthermore, the novel HCH-based pHVI technique satisfies multi-objective HVI properties allowing previous applications of the HVI to be applied to multi-objective parametric optimization. This contribution enables the field of parametric optimization, and thus parametric design, to benefit from prior and future advances in the multi-objective optimization domain involving the HVI.
一种计算参数化超卷指标的新方法
本文提出了一种计算多目标参数数据的超容量指标的新方法。现有的多目标HVI计算技术不能直接用于参数数据,因为设计人员不像对目标那样对参数有偏好。本文提出的新方法允许通过新引入的超锥启发式(HCH)同时考虑目标和参数。这种启发式方法放宽了参数帕累托优势的严格规则,以便在不违反帕累托优势规则的情况下比较不同参数值的设计时进行更实际的优势评估。参数化HVI (pHVI)通过在线和离线评估参数化优化结果,增强了设计工程师的工具包。pHVI测量允许设计人员比较解决方案集,检测优化收敛,并在参数环境中更好地为优化程序提供信息。结果表明,基于hch的pHVI在计算时间的一小部分内产生了与基于支持向量域描述(SVDD)的现有技术相似的质量度量。此外,新的基于hch的pHVI技术满足多目标HVI特性,允许HVI的先前应用应用于多目标参数优化。这一贡献使参数化优化领域,从而参数化设计,受益于涉及HVI的多目标优化领域的先前和未来的进展。
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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