Performance comparison of two recently proposed copositivity tests
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 per...
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Format: | Article |
Language: | English |
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Elsevier
2022-01-01
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Series: | EURO Journal on Computational Optimization |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2192440622000132 |
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author | Bo Peng |
author_facet | Bo Peng |
author_sort | Bo Peng |
collection | DOAJ |
description | 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. |
first_indexed | 2024-04-13T05:07:58Z |
format | Article |
id | doaj.art-2c7550089e564e2aaa61ce4cfebeeff3 |
institution | Directory Open Access Journal |
issn | 2192-4406 |
language | English |
last_indexed | 2024-04-13T05:07:58Z |
publishDate | 2022-01-01 |
publisher | Elsevier |
record_format | Article |
series | EURO Journal on Computational Optimization |
spelling | doaj.art-2c7550089e564e2aaa61ce4cfebeeff32022-12-22T03:01:07ZengElsevierEURO Journal on Computational Optimization2192-44062022-01-0110100037Performance comparison of two recently proposed copositivity testsBo Peng0VGSCO, University of Vienna, 1090 Wien, AustriaRecently 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.http://www.sciencedirect.com/science/article/pii/S2192440622000132Copositive matrixCopositive programmingMixed-integer linear programming |
spellingShingle | Bo Peng Performance comparison of two recently proposed copositivity tests EURO Journal on Computational Optimization Copositive matrix Copositive programming Mixed-integer linear programming |
title | Performance comparison of two recently proposed copositivity tests |
title_full | Performance comparison of two recently proposed copositivity tests |
title_fullStr | Performance comparison of two recently proposed copositivity tests |
title_full_unstemmed | Performance comparison of two recently proposed copositivity tests |
title_short | Performance comparison of two recently proposed copositivity tests |
title_sort | performance comparison of two recently proposed copositivity tests |
topic | Copositive matrix Copositive programming Mixed-integer linear programming |
url | http://www.sciencedirect.com/science/article/pii/S2192440622000132 |
work_keys_str_mv | AT bopeng performancecomparisonoftworecentlyproposedcopositivitytests |