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Declarative local-search neighbourhoods in MiniZinc
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (Optimisation)ORCID iD: 0000-0002-8032-5774
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (Optimisation)ORCID iD: 0000-0001-8730-4098
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (Optimisation)
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2018 (English)In: PROCEEDINGS OF THE 2018 IEEE 30TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), IEEE Computer Society, 2018, p. 98-105Conference paper, Published paper (Refereed)
Abstract [en]

The aim of solver-independent modelling is to create a model of a satisfaction or optimisation problem independent of a particular technology. This avoids early commitment to a solving technology and allows easy comparison of technologies. MiniZinc is a solver-independent modelling language, supported by CP, MIP, SAT, SMT, and constraint-based local search (CBLS) backends. Some technologies, in particular CP and CBLS, require not only a model but also a search strategy. While backends for these technologies offer default search strategies, it is often beneficial to include in a model a user-specified search strategy for a particular technology, especially if the strategy can encapsulate knowledge about the problem structure. This is complex since a local-search strategy (comprising a neighbourhood, a heuristic, and a meta-heuristic) is often tightly tied to the model. Hence we wish to use the same language for specifying the model and the local search. We show how to extend MiniZinc so that one can attach a fully declarative neighbourhood specification to a model, while maintaining the solver-independence of the language. We explain how to integrate a model-specific declarative neighbourhood with an existing CBLS backend for MiniZinc.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018. p. 98-105
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-368077DOI: 10.1109/ICTAI.2018.00025ISI: 000457750200015ISBN: 978-1-5386-7449-9 (electronic)OAI: oai:DiVA.org:uu-368077DiVA, id: diva2:1267575
Conference
30th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), NOV 05-07, 2018, Volos, GREECE
Funder
Swedish Research Council, 2015-04910Available from: 2018-12-17 Created: 2018-12-03 Last updated: 2019-02-28Bibliographically approved

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Björdal, GustavFlener, PierrePearson, Justin

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