Estimating scalability issues while finding an optimal assignment for carpooling

Luk Knapen, Daniel Keren, Ansar Ul Haque Yasar, Sungjin Cho, Tom Bellemans, Davy Janssens, Geert Wets

Research output: Contribution to journalConference articlepeer-review

Abstract

An automatic service to match commuting trips has been designed. Candidate carpoolers register their personal profile and a set of periodically recurring trips. The Global CarPooling Matching Service (GCPMS) shall advise registered candidates on how to combine their commuting trips by carpooling. Planned periodic trips correspond to nodes in a graph; the edges are labeled with the probability for negotiation success while trying to merge planned trips by carpooling. The probability values are calculated by a learning mechanism using on one hand the registered person and trip characteristics and on the other hand the negotiation feedback. The GCPMS provides advice by maximizing the expected value for negotiation success. This paper describes possible ways to determine the optimal advice and estimates computational scalability using real data for Flanders.

Original languageEnglish
Pages (from-to)372-379
Number of pages8
JournalProcedia Computer Science
Volume19
DOIs
StatePublished - 2013
Event4th International Conference on Ambient Systems, Networks and Technologies, ANT 2013 and the 3rd International Conference on Sustainable Energy Information Technology, SEIT 2013 - Halifax, NS, Canada
Duration: 25 Jun 201328 Jun 2013

Bibliographical note

Funding Information:
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement nr 270833.

Keywords

  • Agent-based modeling
  • Dynamic networks
  • Graph theory
  • Learning
  • Scalability

ASJC Scopus subject areas

  • Computer Science (all)

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