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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18430

Title: Scalability issues in optimal assignment for carpooling
Authors: KNAPEN, Luk
Hartman, Irith Ben-Arroyo
Keren, Daniel
YASAR, Ansar
CHO, Sungjin
BELLEMANS, Tom
JANSSENS, Davy
WETS, Geert
Issue Date: 2015
Citation: JOURNAL OF COMPUTER AND SYSTEM SCIENCES, 81 (3), p. 568-584
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).
Notes: E-mail Addresses:luk.knapen@uhasselt.be
URI: http://hdl.handle.net/1942/18430
Link to publication: http://www.sciencedirect.com/science/article/pii/S0022000014001512
DOI: 10.1016/j.jcss.2014.11.010
ISI #: 000348248100007
ISSN: 0022-0000
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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