CIRG@UP OptiBench: a statistically sound framework for benchmarking optimisation algorithms

E. Peer, A. Engelbrecht, F. V. D. Bergh
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引用次数: 6

Abstract

This article is a proposal, by the Computational Intelligence Research Group at the University of Pretoria (CIRG@UP), for a framework to benchmark optimisation algorithms. This framework, known as OptiBench, was conceived out of the necessity to consolidate the efforts of a large research group. Many problems arise when different people work independently on their own research initiatives. These problems range from duplicating effort to, more seriously, having conflicting results. In addition, less experienced members of the group are sometimes unfamiliar with the necessary statistical methods required to properly analyse their results. These problems are not limited internally to CIRG@UP but are also prevalent in the research community at large. This proposal aims to standardise the research methodology used by CIRG@UP internally (initially in the optimisation subgroup and later in subgroups working in other paradigms of computational research). Obviously this article cannot dictate the methodologies that should be used by other members of the broader research community, however, the hope is that this framework can be found useful and that others would willingly contribute and become involved.
CIRG@UP OptiBench:一个统计上健全的基准优化算法框架
本文是比勒陀利亚大学计算智能研究小组(CIRG@UP)提出的一项建议,旨在建立一个基准优化算法的框架。这个框架被称为OptiBench,是为了巩固一个大型研究小组的努力而构想出来的。当不同的人在各自的研究计划中独立工作时,会出现许多问题。这些问题的范围从重复的努力到更严重的结果相互冲突。此外,该小组经验不足的成员有时不熟悉适当分析其结果所需的必要统计方法。这些问题不仅局限于CIRG@UP内部,而且在整个研究界也很普遍。本提案旨在标准化CIRG@UP内部使用的研究方法(最初在优化子组中,后来在其他计算研究范式的子组中工作)。显然,本文不能规定应该由更广泛的研究社区的其他成员使用的方法,但是,希望这个框架可以被发现是有用的,并且其他人愿意贡献并参与其中。
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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