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多目标信赖域算法MHT的数值结果。

Numerical results for the multiobjective trust region algorithm MHT.

作者信息

Thomann Jana, Eichfelder Gabriele

机构信息

Institute for Mathematics, Technische Universität Ilmenau, Ilmenau, Germany.

出版信息

Data Brief. 2019 Jun 6;25:104103. doi: 10.1016/j.dib.2019.104103. eCollection 2019 Aug.

Abstract

In this data article, we report data and numerical results related to the research article entitled "A trust region algorithm for heterogeneous multiobjective optimization" by Thomann and Eichfelder in SIAM Journal on Optimization. The method MHT which is presented there is designed for multiobjective heterogeneous optimization problems where one of the objective functions is an expensive black-box function, for example given by a time-consuming simulation. Here, we present the data of numerical tests with a set of 78 test problems mainly collected from literature and only complemented by few self-chosen test problems. The presence of expensive functions is artificially introduced in the test problems by defining one of the objective functions as expensive.

摘要

在本数据文章中,我们报告了与托曼和艾希费尔德发表于《工业与应用数学学会优化杂志》上的题为《一种用于异构多目标优化的信赖域算法》的研究文章相关的数据和数值结果。文中提出的MHT方法是为多目标异构优化问题设计的,其中一个目标函数是昂贵的黑箱函数,例如由耗时的模拟给出。在此,我们展示了一组主要从文献中收集并仅补充了少量自行选择的测试问题的78个测试问题的数值测试数据。通过将其中一个目标函数定义为昂贵函数,在测试问题中人为引入了昂贵函数的存在。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a340/6614729/69bfc29a2215/gr1.jpg

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