GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations
Abstract In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introduce a general optimization management tool called GloMPO (Globally Managed Paralle...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-02-01
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| Series: | Journal of Cheminformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13321-022-00581-z |
| _version_ | 1819279725058588672 |
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| author | Michael Freitas Gustavo Toon Verstraelen |
| author_facet | Michael Freitas Gustavo Toon Verstraelen |
| author_sort | Michael Freitas Gustavo |
| collection | DOAJ |
| description | Abstract In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introduce a general optimization management tool called GloMPO (Globally Managed Parallel Optimization) to help address some of the challenges faced by practitioners. GloMPO manages and shares information between traditional optimization algorithms run in parallel. We hope that GloMPO will be a flexible framework which allows for customization and hybridization of various optimization ideas, while also providing a substitute for human interventions and decisions which are a common feature of optimization processes of hard problems. GloMPO is shown to produce lower minima than traditional optimization approaches on global optimization test functions, the Lennard-Jones cluster problem, and ReaxFF reparameterizations. The novel feature of forced optimizer termination was shown to find better minima than normal optimization. GloMPO is also shown to provide qualitative benefits such a identifying degenerate minima, and providing a standardized interface and workflow manager. |
| first_indexed | 2024-12-24T00:32:28Z |
| format | Article |
| id | doaj.art-8e1652f539a4485d9eee59140bdba95e |
| institution | Directory Open Access Journal |
| issn | 1758-2946 |
| language | English |
| last_indexed | 2024-12-24T00:32:28Z |
| publishDate | 2022-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Cheminformatics |
| spelling | doaj.art-8e1652f539a4485d9eee59140bdba95e2022-12-21T17:24:13ZengBMCJournal of Cheminformatics1758-29462022-02-0114112910.1186/s13321-022-00581-zGloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizationsMichael Freitas Gustavo0Toon Verstraelen1Center for Molecular Modeling, Ghent UniversityCenter for Molecular Modeling, Ghent UniversityAbstract In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introduce a general optimization management tool called GloMPO (Globally Managed Parallel Optimization) to help address some of the challenges faced by practitioners. GloMPO manages and shares information between traditional optimization algorithms run in parallel. We hope that GloMPO will be a flexible framework which allows for customization and hybridization of various optimization ideas, while also providing a substitute for human interventions and decisions which are a common feature of optimization processes of hard problems. GloMPO is shown to produce lower minima than traditional optimization approaches on global optimization test functions, the Lennard-Jones cluster problem, and ReaxFF reparameterizations. The novel feature of forced optimizer termination was shown to find better minima than normal optimization. GloMPO is also shown to provide qualitative benefits such a identifying degenerate minima, and providing a standardized interface and workflow manager.https://doi.org/10.1186/s13321-022-00581-zReaxFFGlobal optimizationReparameterizationBlack-box optimizationPythonParallel computation |
| spellingShingle | Michael Freitas Gustavo Toon Verstraelen GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations Journal of Cheminformatics ReaxFF Global optimization Reparameterization Black-box optimization Python Parallel computation |
| title | GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations |
| title_full | GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations |
| title_fullStr | GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations |
| title_full_unstemmed | GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations |
| title_short | GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations |
| title_sort | glompo globally managed parallel optimization a tool for expensive black box optimizations application to reaxff reparameterizations |
| topic | ReaxFF Global optimization Reparameterization Black-box optimization Python Parallel computation |
| url | https://doi.org/10.1186/s13321-022-00581-z |
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