Performance comparison of two recently proposed copositivity tests

IF 2.6 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE EURO Journal on Computational Optimization Pub Date : 2022-01-01 DOI:10.1016/j.ejco.2022.100037
Bo Peng
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引用次数: 0

Abstract

Recently and simultaneously, two MILP-based approaches to copositivity testing were proposed. This note tries a performance comparison, using a group of test sets containing a large number of designed instances. According to the numerical results, we find that one copositivity detection approach performs better when the function value of the defined function h of a matrix is large while the other one performs better when the dimension of problems is increasing moderately. A problem set that is hard for both approaches is also presented, which may be used as a test bed for future competing approaches. An improved variant of one of the approaches is also proposed to handle those hard instances more efficiently.

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最近提出的两种复合率测试的性能比较
最近,同时提出了两种基于milp的组合性测试方法。本文尝试使用一组包含大量设计实例的测试集进行性能比较。数值结果表明,当矩阵的定义函数h的函数值较大时,一种检测方法性能较好,而当问题的维数适度增加时,另一种检测方法性能较好。本文还提出了一个两种方法都难以解决的问题集,它可以作为未来竞争方法的测试平台。为了更有效地处理这些困难实例,还提出了其中一种方法的改进变体。
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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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