PDFO: a cross-platform package for Powell’s derivative-free optimization solvers
The late Professor M. J. D. Powell devised five trust-region methods for derivative-free optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully implemented them into publicly available solvers, renowned for their robustness and efficiency. However, the solvers were implemented...
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| Published in | Mathematical programming computation Vol. 16; no. 4; pp. 535 - 559 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2024
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1867-2949 1867-2957 1867-2957 |
| DOI | 10.1007/s12532-024-00257-9 |
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| Abstract | The late Professor M. J. D. Powell devised five trust-region methods for derivative-free optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully implemented them into publicly available solvers, renowned for their robustness and efficiency. However, the solvers were implemented in Fortran 77 and hence may not be easily accessible to some users. We introduce the PDFO package, which provides user-friendly Python and MATLAB interfaces to Powell’s code. With PDFO, users of such languages can call Powell’s Fortran solvers easily without dealing with the Fortran code. Moreover, PDFO includes bug fixes and improvements, which are particularly important for handling problems that suffer from ill-conditioning or failures of function evaluations. In addition to the PDFO package, we provide an overview of Powell’s methods, sketching them from a uniform perspective, summarizing their main features, and highlighting the similarities and interconnections among them. We also present experiments on PDFO to demonstrate its stability under noise, tolerance of failures in function evaluations, and potential to solve certain hyperparameter optimization problems. |
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| AbstractList | The late Professor M. J. D. Powell devised five trust-region methods for derivative-free optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully implemented them into publicly available solvers, renowned for their robustness and efficiency. However, the solvers were implemented in Fortran 77 and hence may not be easily accessible to some users. We introduce the PDFO package, which provides user-friendly Python and MATLAB interfaces to Powell’s code. With PDFO, users of such languages can call Powell’s Fortran solvers easily without dealing with the Fortran code. Moreover, PDFO includes bug fixes and improvements, which are particularly important for handling problems that suffer from ill-conditioning or failures of function evaluations. In addition to the PDFO package, we provide an overview of Powell’s methods, sketching them from a uniform perspective, summarizing their main features, and highlighting the similarities and interconnections among them. We also present experiments on PDFO to demonstrate its stability under noise, tolerance of failures in function evaluations, and potential to solve certain hyperparameter optimization problems. |
| Author | Zhang, Zaikun Ragonneau, Tom M. |
| Author_xml | – sequence: 1 givenname: Tom M. orcidid: 0000-0003-2717-2876 surname: Ragonneau fullname: Ragonneau, Tom M. organization: Department of Applied Mathematics, The Hong Kong Polytechnic University – sequence: 2 givenname: Zaikun orcidid: 0000-0001-8934-8190 surname: Zhang fullname: Zhang, Zaikun email: zaikunzhang@gmail.com organization: Department of Applied Mathematics, The Hong Kong Polytechnic University |
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| Keywords | 65K05 90C30 90-04 COBYLA UOBYQA 90C56 NEWUOA BOBYQA LINCOA Derivative-free optimization |
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| SubjectTerms | FORTRAN Full Length Paper Ill-conditioned problems (mathematics) Mathematics Mathematics and Statistics Mathematics of Computing Noise tolerance Operations Research/Decision Theory Optimization Python Solvers Theory of Computation |
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| Title | PDFO: a cross-platform package for Powell’s derivative-free optimization solvers |
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