Computational advances in polynomial optimization: RAPOSa, a freely available global solver

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2022_jogo_gonzalez_computational.pdf (3.18 MB)
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URI: http://hdl.handle.net/10347/29971
ISSN: 0925-5001
E-ISSN: 1573-2916
DOI: 10.1007/s10898-022-01229-w

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2022

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Springer
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In this paper we introduce RAPOSa, a global optimization solver specifically designed for (continuous) polynomial programming problems with box-constrained variables. Written entirely in C++, RAPOSa is based on the Reformulation-Linearization (Sherali and Tuncbilek in J Glob Optim 103:225–249, 1992). We present a description of the main characteristics of RAPOSa along with a thorough analysis of the impact on its performance of various enhancements discussed in the literature, such as bound tightening and SDP cuts. We also present a comparative study with three of the main state-of-the-art global optimization solvers: BARON, Couenne and SCIP

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Global optimization| Polynomial programming| Reformulation-Linearization Technique (RLT)

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González-Rodríguez, B., Ossorio-Castillo, J., González-Díaz, J. et al. Computational advances in polynomial optimization: RAPOSa, a freely available global solver. J Glob Optim (2022). https://doi.org/10.1007/s10898-022-01229-w

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This research has been funded by FEDER and the Spanish Ministry of Science and Technology through Projects MTM2014-60191-JIN, MTM2017-87197-C3 (1-P and 3-P) and PID2021-124030NB-C32. Brais González-Rodríguez acknowledges support from the Spanish Ministry of Education through FPU Grant 17/02643. David R. Penas’ research is funded by the Xunta de Galicia (post-doctoral contract 2019-2022). Ángel M. González-Rueda acknowledges support from the Xunta de Galicia through the ERDF (ED431C-2020-14 and ED431G 2019/01) and “CITIC”. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.

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© 2022 The Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
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Estatística, Análise Matemática e Optimización