无衍生 DIRECT 类型方法实用性回顾与计算研究

IF 3.3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Informatica Pub Date : 2024-03-26 DOI:10.15388/24-infor548
Linas Stripinis, Remigijus Paulavičius
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引用次数: 0

摘要

无衍生 DIRECT 型全局优化算法因其简单有效,在应对现实世界的优化挑战时越来越受到青睐。本综述通过对科学期刊和计算研究的系统分析,探讨了这些算法的实际应用。在实际问题中,我们尤其发现了可重复性方面的重大挑战。为了解决这个问题,我们利用著名的 CEC 库中的实际问题进行了一项实验研究,将 DIRECT 型技术与最先进的对应技术进行了比较。因此,这项研究揭示了这一领域目前存在的差距、机遇和未来的高级研究前景,为复制和扩展本文介绍的研究成果奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review and Computational Study on Practicality of Derivative-Free DIRECT-Type Methods
Derivative-free DIRECT-type global optimization algorithms are increasingly favoured for their simplicity and effectiveness in addressing real-world optimization challenges. This review examines their practical applications through a systematic analysis of scientific journals and computational studies. In particular, significant challenges in reproducibility have been identified with practical problems. To address this, we conducted an experimental study using practical problems from reputable CEC libraries, comparing DIRECT-type techniques against their state-of-the-art counterparts. Therefore, this study sheds light on current gaps, opportunities, and future prospects for advanced research in this domain, laying the foundation for replicating and expanding the research findings presented herein. PDF  XML
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来源期刊
Informatica
Informatica 工程技术-计算机:信息系统
CiteScore
5.90
自引率
6.90%
发文量
19
审稿时长
12 months
期刊介绍: The quarterly journal Informatica provides an international forum for high-quality original research and publishes papers on mathematical simulation and optimization, recognition and control, programming theory and systems, automation systems and elements. Informatica provides a multidisciplinary forum for scientists and engineers involved in research and design including experts who implement and manage information systems applications.
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