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Interval constraint programming for globally solving catalog-based categorical optimization

  • In this article, we propose an interval constraint programming method for globally solving catalog-based categorical optimization problems. It supports catalogs of arbitrary size and properties of arbitrary dimension, and does not require any modeling effort from the user. A novel catalog-based contractor (or filtering operator) guarantees consistency between the categorical properties and the existing catalog items. This results in an intuitive and generic approach that is exact, rigorous (robust to roundoff errors) and can be easily implemented in an off-the-shelf interval-based continuous solver that interleaves branching and constraint propagation. We demonstrate the validity of the approach on a numerical problem in which a categorical variable is described by a two-dimensional property space. A Julia prototype is available as open-source software under the MIT license.

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Metadaten
Author:Charlie Vanaret
Document Type:Article
Parent Title (English):Journal of Global Optimization
Volume:89
First Page:457
Last Page:476
Year of first publication:2024
ArXiv Id:http://arxiv.org/abs/2104.03652
DOI:https://doi.org/10.1007/s10898-023-01362-0
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