Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Constraint-based lagrangian relaxation

Simple item page
dc.contributor.authorFontaine, Daniel
dc.contributor.authorMichel, Laurent
dc.contributor.authorVan Hentenryck, Pascal
dc.coverage.spatialLyon France
dc.date.accessioned2015-12-13T22:31:31Z
dc.date.createdSeptember 8-12 2014
dc.date.issued2014
dc.date.updated2015-12-11T09:01:12Z
dc.description.abstractThis paper studies how to generalize Lagrangian relaxation to high-level optimization models, including constraint-programming and local search models. It exploits the concepts of constraint violation (typically used in constraint programming and local search) and constraint satisfiability (typically exploited in mathematical programming). The paper considers dual and primal methods, studies their properties, and discusses how they can be implemented in terms of high-level model combinators and algorithmic templates. Experimental results suggest the potential benefits of Lagrangian methods for improving high-level constraint programming and local search models.
dc.identifier.isbn9783319104270
dc.identifier.urihttp://hdl.handle.net/1885/75287
dc.publisherSpringer Verlag
dc.relation.ispartofseries20th International Conference on the Principles and Practice of Constraint Programming, CP 2014
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleConstraint-based lagrangian relaxation
dc.typeConference paper
local.bibliographicCitation.lastpage339
local.bibliographicCitation.startpage324
local.contributor.affiliationFontaine, Daniel, University of Connecticut
local.contributor.affiliationMichel, Laurent, University of Connecticut
local.contributor.affiliationVan Hentenryck, Pascal, College of Engineering and Computer Science, ANU
local.contributor.authoruidVan Hentenryck, Pascal, u5136864
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080200 - COMPUTATION THEORY AND MATHEMATICS
local.identifier.ariespublicationU3488905xPUB4554
local.identifier.doi10.1007/978-3-319-10428-7_25
local.identifier.scopusID2-s2.0-84906232704
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
01_Fontaine_Constraint-based_lagrangian_2014.pdf
Size:
311.32 KB
Format:
Adobe Portable Document Format
Download

Collections

ANU Research Publications

DSpace software copyright © 2002-2026 LYRASIS