Scalability issues in optimal assignment for carpooling

Luk Knapen, Irith Ben-Arroyo Hartman, Daniel Keren, Ansar Ul Haque Yasar, Sungjin Cho, Tom Bellemans, Davy Janssens, Geert Wets

Research output: Contribution to journalArticlepeer-review

Abstract

Carpooling for commuting can save cost and helps in reducing pollution. An automatic Web based Global CarPooling Matching Service (GCPMS) for matching commuting trips has been designed. The service supports carpooling candidates by supplying advice during their exploration for potential partners. Such services collect data about the candidates, and base their advice for each pair of trips to be combined, on an estimate of the probability for successful negotiation between the candidates to carpool. 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 problem of maximizing the expected value of carpooling negotiation success was formulated and was proved to be NP-hard. In addition, the network characteristics for a realistic case have been analyzed. The carpooling network was established using results predicted by the operational FEATHERS activity based model for Flanders (Belgium).

Original languageEnglish
Pages (from-to)568-584
Number of pages17
JournalJournal of Computer and System Sciences
Volume81
Issue number3
DOIs
StatePublished - 1 May 2015

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 .

Publisher Copyright:
© 2014 Elsevier Inc.

Keywords

  • Activity-based model
  • Agent-based modeling
  • Dynamic networks
  • Graph theory
  • Learning
  • Scalability
  • Star forest
  • Star partition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Applied Mathematics

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