Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14392
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dc.contributor.authorKeren, Daniel-
dc.contributor.authorYASAR, Ansar-
dc.contributor.authorKNAPEN, Luk-
dc.contributor.authorCHO, Sungjin-
dc.contributor.authorBELLEMANS, Tom-
dc.contributor.authorJANSSENS, Davy-
dc.contributor.authorWETS, Geert-
dc.contributor.authorSchuster, Assaf-
dc.contributor.authorSharfman, Izchak-
dc.date.accessioned2012-11-19T10:44:18Z-
dc.date.available2012-11-19T10:44:18Z-
dc.date.issued2012-
dc.identifier.citationShakshuki, Elhadi; Younas, Muhammad (Ed.). ANT 2012 and MobiWIS 2012, Elsevier Science BV, p. 833-839-
dc.identifier.issn1877-0509-
dc.identifier.urihttp://hdl.handle.net/1942/14392-
dc.description.abstractIn this position paper, we exploit the tools from the realm of graph theory to matching and portioning problems of agent population in an agent-based model for traffic and transportation applications. We take the agent-based carpooling application as an example scenario. The first problem is matching, which concerns finding the optimal pairing among agents. The second problem is partitioning, which is crucial for achieving scalability and for other problems that can be parallelized by separating the passenger population to subpopulations such that the interaction between different sub-populations is minimal. Since in real-life applications the agent population, as well as their preferences, very often change, we also discuss incremental solutions to these problems.-
dc.language.isoen-
dc.publisherElsevier Science BV-
dc.relation.ispartofseriesProcedia Computer Science-
dc.rights2012 Published by Elsevier Ltd. Open access under CC BY-NC-ND.-
dc.subject.otherCarpooling-
dc.subject.otherScalability-
dc.subject.otherAgent-based-
dc.subject.otherModeling-
dc.subject.otherMatching-
dc.subject.otherPartitioning-
dc.subject.otherGraph theory-
dc.titleExploiting graph-theorectic tools for matching and partitioning of agent population in an agent-based model for traffic and transportation applications-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsShakshuki, Elhadi-
local.bibliographicCitation.authorsYounas, Muhammad-
local.bibliographicCitation.conferencedate2012, August 27-28-
local.bibliographicCitation.conferencenameThe 1st International Workshop on Agent-based Mobility, Traffic and Transportation Models, Methodologies and Applications-
local.bibliographicCitation.conferenceplaceNiagara Falls (Ontario) - Canada-
dc.identifier.epage839-
dc.identifier.spage833-
dc.identifier.volume10-
local.format.pages7-
local.bibliographicCitation.jcatC1-
local.publisher.placeSARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS-
dc.relation.referencesNiels Agatz, Alan Erera, Martin Savelsbergh and Xing Wang (2010). The Value of Optimization in Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta. ERIM REPORT SERIES RESEARCH IN MANAGEMENT ERS-2010-034-LIS. Gyozo Gidofalvi, Gergely Herenyi, and Torben Bach Pedersen (2008).Instant Social Ride-Sharing. Proc. 15th World Congress on Intelligent Transport Systems, p 8, Intelligent Transportation Society of America. Roberto Baldacci, Vittorio Maniezzo and Aristide Mingozzi (2004). An Exact Method for the Car Pooling Problem Based on Lagrangean Column Generation. Operations Research, Volume 52 Issue 3, June 2004. Sophie N. Parragh, Karl F. Doerner and Richard F. Hartl. A survey on pickup and delivery problems: Part I: Transportation between customers and depot, Part II: Transportation between pickup and delivery locations. Journal für Betriebswirtschaft 58 (1, April), 21-51 and 58 (2, June), 81-117. James Zou, Sujit Gujar and David Parkes (2010). Tolerable Manipulability in Dynamic Assignment without Money. 24th AAAI Conference on Artificial Intelligence (AAAI’10), 2010. Edmonds and Jack (1965). Paths, trees, and flowers. Canad. J. Math. 17: 449-467. Jianbo Shi and Jitendra Malik (2000). IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888-905. Avraham Levy and Michael Lindenbaum (2000). Sequential Karhunen–Loeve Basis Extraction and its Application to Images. IEEE Transactions on Image Processing, vol. 9(8), 2000, 1371-1374. Muaz Niazi and Amir Hussain. (2011). Agent-based Computing from Multi-agent Systems to Agent-Based Models: A Visual Survey, Springer Scientometrics: 89(2), pp. 479-499.-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.relation.ispartofseriesnr10-
dc.bibliographicCitation.oldjcatC2-
local.identifier.vabbc:vabb:340552-
dc.identifier.doi10.1016/j.procs.2012.06.108-
dc.identifier.isi000314400700102-
local.bibliographicCitation.btitleANT 2012 and MobiWIS 2012-
local.uhasselt.internationalyes-
item.validationecoom 2014-
item.validationvabb 2014-
item.contributorKeren, Daniel-
item.contributorYASAR, Ansar-
item.contributorKNAPEN, Luk-
item.contributorCHO, Sungjin-
item.contributorBELLEMANS, Tom-
item.contributorJANSSENS, Davy-
item.contributorWETS, Geert-
item.contributorSchuster, Assaf-
item.contributorSharfman, Izchak-
item.fullcitationKeren, Daniel; YASAR, Ansar; KNAPEN, Luk; CHO, Sungjin; BELLEMANS, Tom; JANSSENS, Davy; WETS, Geert; Schuster, Assaf & Sharfman, Izchak (2012) Exploiting graph-theorectic tools for matching and partitioning of agent population in an agent-based model for traffic and transportation applications. In: Shakshuki, Elhadi; Younas, Muhammad (Ed.). ANT 2012 and MobiWIS 2012, Elsevier Science BV, p. 833-839.-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
crisitem.journal.issn1877-0509-
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