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

doi:10.1016/j.procs.2013.06.051

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

Department of Computer Science

University of Haifa

Research output: Contribution to journal › Conference article › peer-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 language	American English
Pages (from-to)	372-379
Number of pages	8
Journal	Procedia Computer Science
Volume	19
DOIs	https://doi.org/10.1016/j.procs.2013.06.051
State	Published - 2013
Event	4th 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 2013 → 28 Jun 2013

Keywords

Agent-based modeling
Dynamic networks
Graph theory
Learning
Scalability

All Science Journal Classification (ASJC) codes

General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.procs.2013.06.051

Cite this

@article{edee302082704f659199186cf0c71c7d,

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.",

keywords = "Agent-based modeling, Dynamic networks, Graph theory, Learning, Scalability",

author = "Luk Knapen and Daniel Keren and Yasar, {Ansar Ul Haque} and Sungjin Cho and Tom Bellemans and Davy Janssens and Geert Wets",

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.; 4th International Conference on Ambient Systems, Networks and Technologies, ANT 2013 and the 3rd International Conference on Sustainable Energy Information Technology, SEIT 2013 ; Conference date: 25-06-2013 Through 28-06-2013",

year = "2013",

doi = "10.1016/j.procs.2013.06.051",

language = "American English",

volume = "19",

pages = "372--379",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - Estimating scalability issues while finding an optimal assignment for carpooling

AU - Knapen, Luk

AU - Keren, Daniel

AU - Yasar, Ansar Ul Haque

AU - Cho, Sungjin

AU - Bellemans, Tom

AU - Janssens, Davy

AU - Wets, Geert

N1 - 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.

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

KW - Agent-based modeling

KW - Dynamic networks

KW - Graph theory

KW - Learning

KW - Scalability

UR - http://www.scopus.com/inward/record.url?scp=84896946079&partnerID=8YFLogxK

U2 - 10.1016/j.procs.2013.06.051

DO - 10.1016/j.procs.2013.06.051

M3 - Conference article

SN - 1877-0509

VL - 19

SP - 372

EP - 379

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 4th International Conference on Ambient Systems, Networks and Technologies, ANT 2013 and the 3rd International Conference on Sustainable Energy Information Technology, SEIT 2013

Y2 - 25 June 2013 through 28 June 2013

ER -

Estimating scalability issues while finding an optimal assignment for carpooling

Abstract

Keywords

All Science Journal Classification (ASJC) codes

UN SDGs

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