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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16303

Title: Agent-based modeling for carpooling
Authors: KNAPEN, Luk
YASAR, Ansar
CHO, Sungjin
BELLEMANS, Tom
Issue Date: 2014
Publisher: Information Science Reference (an imprint of IGI Global)
Citation: Janssens, Davy ; Yasar, Ansar-Ul-Haque ; Knapen, Luk (Ed.). Data Science and Simulation in Transportation Research, p. 232-258
Series/Report: Advances in Data Mining and Database Management (ADMDM) Book Series
Abstract: Modeling activities and travel for individuals in order to estimate traffic demand leads to large scale simulations. Most current models simulate individuals acting in a mutually independent way except for the use of the shared transportation infrastructure. As soon as cooperation between autonomous individuals is accounted for, the individuals are linked to each other in a network structure and interact with their neighbours in the network while trying to achieve their own goals. In concrete traffic-related problems, those networks can grow very large. Optimization over such networks typically leads to combinatorially explosive problems. In this chapter, the case of providing optimal advice to combine carpooling candidates is considered. First, the advisor software structure is explained; then, the characteristics for the carpooling candidates network derived for Flanders (Belgium) are calculated in order to estimate the problem size.
URI: http://hdl.handle.net/1942/16303
Link to publication: http://www.igi-global.com/book/data-science-simulation-transportation-research/78944#table-of-contents
DOI: 10.4018/978-1-4666-4920-0.ch012
ISI #: 000364530200014
ISBN: 9781466649200
ISSN: 2327-1981
Category: B2
Type: Book Section
Validation: vabb, 2017
Appears in Collections: Research publications

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