Hybridizing two linear relaxation techniques in interval-based solvers
Abstract In deterministic global optimization, techniques for linear relaxation of a non-convex program are used in the lower bound calculation phase. To achieve this phase, most deterministic global optimization codes use reformulation-linearization techniques. However, there exist also two interval-based polyhedral relaxation techniques which produce reliable bounds without adding new auxiliary variables, and which can take into account mathematical operations and most transcendental functions: (i) the affine relaxation technique, used in the IBBA code, based on affine forms and affine arithmetic, and (ii) the extremal Taylor technique, used in the Ibex-Opt code, which is based on a specific interval-based Taylor form. In this paper, we describe how these two interval-based linear relaxation techniques can be hybridized. These two approaches appear to be complementary, and such a hybrid method performs well on a representative sample of constrained global optimization instances.
Authors
- Gilles Trombettoni (ORCID: https://orcid.org/0000-0002-5283-7203)
- Ignacio Araya (ORCID: https://orcid.org/0000-0001-5882-6217)
- Jordan Ninin (ORCID: https://orcid.org/0000-0002-7232-8246)
- Frédéric Messine (ORCID: https://orcid.org/0000-0002-6457-3321)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Pontificia Universidad Católica de Valparaíso (CL)
- Université de Bretagne Occidentale (FR)
- Université Fédérale de Toulouse Midi-Pyrénées (FR)
- Université de Montpellier (FR)
- Institut National Polytechnique de Toulouse (FR)
- Laboratoire Plasma et Conversion d'Energie (FR)
- Laboratoire des Sciences et Techniques de l’Information de la Communication et de la Connaissance (FR)
- École nationale supérieure de techniques avancées Bretagne (FR)
- École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des Télécommunications (FR)
Publication Details
- Journal
- Journal of Global Optimization
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1007/s10898-024-01449-2
- Citations
- 1
- Primary Topic
- Numerical Methods and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.36