Title
Estimating Scalability Issues While Finding an Optimal Assignment for Carpooling.
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.
Year
DOI
Venue
2013
10.1016/j.procs.2013.06.051
Procedia Computer Science
Keywords
Field
DocType
Graph theory,Agent-based modeling,Scalability,Dynamic networks,Learning
Graph theory,Data mining,Graph,Computer science,Expected value,Artificial intelligence,Merge (version control),TRIPS architecture,Periodic graph (geometry),Machine learning,Negotiation,Scalability
Conference
Volume
ISSN
Citations 
19
1877-0509
5
PageRank 
References 
Authors
0.71
2
7
Name
Order
Citations
PageRank
Luk Knapen18622.42
Daniel Keren2931116.90
Ansar-Ul-Haque Yasar311842.31
Sungjin Cho4366.49
Tom Bellemans57323.16
Davy Janssens623838.08
Geert Wets776667.59