IntRoute: An Integer Programming Based Approach for Best Bus Route Discovery

Sung, CW; Yang, X; Liao, CS; Liu, W

IntRoute: An Integer Programming Based Approach for Best Bus Route Discovery

Sung, CW Yang, X

Liao, CS Liu, W

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Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Database Systems for Advanced Applications, 2021, 12683 LNCS, pp. 604-607
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.author	Sung, CW
dc.contributor.author	Yang, X https://orcid.org/0000-0001-6487-3183
dc.contributor.author	Liao, CS
dc.contributor.author	Liu, W https://orcid.org/0000-0002-3003-1313
dc.date	2021-04-11
dc.date.accessioned	2022-06-13T01:24:25Z
dc.date.available	2022-06-13T01:24:25Z
dc.date.issued	2021-01-01
dc.identifier.citation	Database Systems for Advanced Applications, 2021, 12683 LNCS, pp. 604-607
dc.identifier.isbn	9783030731991
dc.identifier.issn	0302-9743
dc.identifier.issn	1611-3349
dc.identifier.uri	http://hdl.handle.net/10453/158136
dc.description.abstract	An efficient data-driven public transportation system can improve urban potency. In this research, we propose IntRoute, an Integer Programming (IP) based approach to optimize bus route planning. Specifically, IntRoute first contracts bus stops via clustering and then derives a new bus route via a mixed integer linear program (ILP). This two-phase strategy brings three major merits, i.e., a single bus route without any transfer, the minimal total time consuming, and an efficient optimization algorithm for large-scale problems. Experimental results show that our IntRoute significantly reduces the traditional commuting time in Sydney from 31.53 min down to 18.06 min on average.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Database Systems for Advanced Applications
dc.relation.ispartof	International Conference on Database Systems for Advanced Applications
dc.relation.ispartofseries	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.isbasedon	10.1007/978-3-030-73200-4_44
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	IntRoute: An Integer Programming Based Approach for Best Bus Route Discovery
dc.type	Conference Proceeding
utslib.citation.volume	12683 LNCS
utslib.location.activity	Taipei, Taiwan,
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-06-13T01:24:24Z
pubs.finish-date	2021-04-14
pubs.place-of-publication	Switzerland
pubs.publication-status	Published
pubs.start-date	2021-04-11
pubs.volume	12683 LNCS
dc.location	Switzerland

Abstract:

An efficient data-driven public transportation system can improve urban potency. In this research, we propose IntRoute, an Integer Programming (IP) based approach to optimize bus route planning. Specifically, IntRoute first contracts bus stops via clustering and then derives a new bus route via a mixed integer linear program (ILP). This two-phase strategy brings three major merits, i.e., a single bus route without any transfer, the minimal total time consuming, and an efficient optimization algorithm for large-scale problems. Experimental results show that our IntRoute significantly reduces the traditional commuting time in Sydney from 31.53 min down to 18.06 min on average.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/158136