Two decades of blackbox optimization applications

IF 2.6 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Stéphane Alarie , Charles Audet , Aïmen E. Gheribi , Michael Kokkolaras , Sébastien Le Digabel
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引用次数: 46

Abstract

This article reviews blackbox optimization applications of direct search optimization methods over the past twenty years. Emphasis is placed on the Mesh Adaptive Direct Search (Mads) derivative-free optimization algorithm. The main focus is on applications in three specific fields: energy, materials science, and computational engineering design. Nevertheless, other applications in science and engineering, including patents, are also considered. The breadth of applications demonstrates the versatility of Mads and highlights the evolution of its accompanying software NOMAD as a standard tool for blackbox optimization.

二十年的黑箱优化应用
本文回顾了近二十年来直接搜索优化方法在黑盒优化中的应用。重点介绍了网格自适应直接搜索(Mads)无导数优化算法。主要关注三个特定领域的应用:能源、材料科学和计算工程设计。然而,科学和工程方面的其他应用,包括专利,也被考虑在内。应用的广度展示了Mads的多功能性,并突出了其配套软件NOMAD作为黑盒优化标准工具的演变。
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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来源期刊
EURO Journal on Computational Optimization
EURO Journal on Computational Optimization OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
3.50
自引率
0.00%
发文量
28
审稿时长
60 days
期刊介绍: The aim of this journal is to contribute to the many areas in which Operations Research and Computer Science are tightly connected with each other. More precisely, the common element in all contributions to this journal is the use of computers for the solution of optimization problems. Both methodological contributions and innovative applications are considered, but validation through convincing computational experiments is desirable. The journal publishes three types of articles (i) research articles, (ii) tutorials, and (iii) surveys. A research article presents original methodological contributions. A tutorial provides an introduction to an advanced topic designed to ease the use of the relevant methodology. A survey provides a wide overview of a given subject by summarizing and organizing research results.
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