The G12 project: mapping solver independent models to efficient solutions

dc.contributor.authorStuckey, Peter J
dc.contributor.authorGarcia de la Banda, Maria
dc.contributor.authorMaher, Michael
dc.contributor.authorMarriott, Kim
dc.contributor.authorSlaney, John K
dc.contributor.authorSomogyi, Zoltan
dc.contributor.authorWallace, Mark
dc.contributor.authorWalsh, Toby
dc.coverage.spatialSitges Spain
dc.date.accessioned2015-12-13T22:58:10Z
dc.date.createdOctober 1-5 2005
dc.date.issued2005
dc.date.updated2015-12-12T07:21:32Z
dc.description.abstractThe G12 project recently started by National IGT Australia (NICTA) is an ambitious project to develop a software platform for solving large scale industrial combinatorial optimisation problems. The core design involves three languages: Zinc, Cadmium and Mercury (Group 12 of the periodic table). Zinc is a declarative modelling language for expressing problems, independent of any solving methodology. Cadmium is a mapping language for mapping Zinc models to underlying solvers and/or search strategies, including hybrid approaches. Finally, existing Mercury will be extended as a language for building extensible and hybridimble solvers. The same Zinc model, used with different Cadmium mappings, will allow us to experiment with different complete, local, or hybrid search approaches for the same problem. This talk will explain the G12 global design, the final G12 objectives, and our progress so far.
dc.identifier.isbn9783540292388
dc.identifier.urihttp://hdl.handle.net/1885/83342
dc.publisherSpringer
dc.relation.ispartofseriesInternational Conference on Principles and Practice of Constraint Programming (CP 2005)
dc.sourceProceedings of International Conference on Principles and Practice of Constraint Programming (CP 2005)
dc.subjectKeywords: Cadmium; Computer software; Mapping; Mathematical models; Problem solving; Cadmium mappings; G12 project; Industrial combinatorial optimization; Software platform; Project management
dc.titleThe G12 project: mapping solver independent models to efficient solutions
dc.typeConference paper
local.bibliographicCitation.lastpage16
local.bibliographicCitation.startpage13
local.contributor.affiliationStuckey, Peter J, National ICT Australia
local.contributor.affiliationGarcia de la Banda, Maria, Monash University
local.contributor.affiliationMaher, Michael, National ICT Australia
local.contributor.affiliationMarriott, Kim, Monash University
local.contributor.affiliationSlaney, John K, College of Engineering and Computer Science, ANU
local.contributor.affiliationSomogyi, Zoltan, National ICT Australia
local.contributor.affiliationWallace, Mark, Monash University
local.contributor.affiliationWalsh, Toby, University of York
local.contributor.authoremailu8800435@anu.edu.au
local.contributor.authoruidSlaney, John K, u8800435
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.ariespublicationMigratedxPub11591
local.identifier.doi10.1007/11564751_4
local.identifier.scopusID2-s2.0-33646187946
local.identifier.uidSubmittedByMigrated
local.type.statusPublished Version

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