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dc.contributor.advisorMiguel, Ian
dc.contributor.advisorAkgun, Ozgur
dc.contributor.authorSpracklen, Patrick
dc.coverage.spatialv, 173 p.en_US
dc.date.accessioned2022-10-26T11:33:10Z
dc.date.available2022-10-26T11:33:10Z
dc.date.issued2022-11-29
dc.identifier.urihttp://hdl.handle.net/10023/26251
dc.description.abstractConstraint Programming (CP) is a powerful technique for solving large-scale combinatorial (optimisation) problems. Solving a problem proceeds in two distinct phases: modelling and solving. Effective modelling has a huge impact on the performance of the solving process. Even with the advance of modern automated modelling tools, search spaces involved can be so vast that problems can still be difficult to solve. To further constrain the model a more aggressive step that can be taken is the addition of streamliner constraints, which are not guaranteed to be sound but are designed to focus effort on a highly restricted but promising portion of the search space. Previously, producing effective streamlined models was a manual, difficult and time-consuming task. This thesis presents a completely automated process to the generation, search and selection of streamliner portfolios to produce a substantial reduction in search effort across a diverse range of problems. First, we propose a method for the generation and evaluation of streamliner conjectures automatically from the type structure present in an Essence specification. Second, the possible streamliner combinations are structured into a lattice and a multi-objective search method for searching the lattice of combinations and building a portfolio of streamliner combinations is defined. Third, the problem of "Streamliner Selection" is introduced which deals with selecting from the portfolio an effective streamliner for an unseen instance. The work is evaluated by presenting two sets of experiments on a variety of problem classes. Lastly, we explore the effect of model selection in the context of streamlined specifications and discuss the process of streamlining for Constrained Optimization Problems.en_US
dc.description.sponsorship"This work was supported by: EPSRC funding award EP/N509759/1" -- Fundingen
dc.language.isoenen_US
dc.subjectConstraint programmingen_US
dc.subjectConstraint modellingen_US
dc.subjectStreamlined constraint reasoningen_US
dc.titleStreamlined constraint reasoning : an automated approach from high level constraint specificationsen_US
dc.typeThesisen_US
dc.contributor.sponsorEngineering and Physical Sciences Research Council (EPSRC)en_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US
dc.identifier.doihttps://doi.org/10.17630/sta/212
dc.identifier.grantnumberEP/N509759/1en_US


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