A distributed dijkstra's algorithm for the implementation of a Real Time Carpooling Service with an optimized aspect on siblings

Sghaier, Manel; Zgaya, Hayfa; Hammadi, Slim; Tahón, Christian

doi:10.1109/itsc.2010.5625288

Cited by 19 publications

(14 citation statements)

References 6 publications

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“…Another approach widely followed in the literature for analyzing carpooling is the agent based model (ABM) [8][9][10][11][12][13]. A multi-ABM in conjunction with Dikstra's algorithm is used in [8] to efficiently answer real time users' queries.…”

Section: Related Workmentioning

confidence: 99%

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Never drive alone: Boosting carpooling with network analysis

Guidotti

Nanni

Rinzivillo

et al. 2017

Information Systems

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Section: Related Workmentioning

confidence: 99%

“…A multi-ABM in conjunction with Dikstra's algorithm is used in [8] to efficiently answer real time users' queries. In [9] an ABM is designed to optimize transports by the ride sharing of people who usually cover the same route.…”

Section: Related Workmentioning

confidence: 99%

Never drive alone: Boosting carpooling with network analysis

Guidotti

Nanni

Rinzivillo

et al. 2017

Information Systems

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“…The fairness component was also neglected in this solution. Another solution which is based on the Dijkstra Algorithm [6]. The network of users is divided into small areas centered on a driver.…”

Section: Literature Surveymentioning

confidence: 99%

Intelligent Carpooling System

Shete¹,

Bhandare²,

Londhe³

et al. 2015

IJCA

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The constant population and economic growth has caused an enormous increase in the number of private cars in cities worldwide. Carpooling is one of the most effective solutions to traffic congestion. In this paper, an advanced carpool system is described in detail and called the intelligent carpool system (ICS), which provides users the use of the carpool services through a smart handheld device anywhere and at any time. To generate ride matches through the carpool service agency, we use the genetic algorithm to propose the geneticbased carpool route and matching algorithm (GCRMA) for this multi objective optimization problem called the carpool service problem (CSP).Use of the GCRMA was proved to result in superior results involving the optimization objectives of CSP than other algorithms. Furthermore, our GCRMA has small amount of computational complexity to response the match results in the reasonable time, and the processing time is further reduced by the termination criteria of early stop. The remaining of this paper is organized as follows: Section I contains introduction to carpool system, Section II presents related search, Section III describes two modules of ICS, Section IV contains carpool system problem (CSP),while Section V contains genetic based algorithm i.e. GCRMA. KeywordsIntelligent carpool system (ICS), genetic-based carpool route and matching algorithm (GCRMA), carpool service problem (CSP).

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“…The population is the same as that of the first test: 119 users going to four different destinations. Case A has a fitness function, which does not account for user preferences whereas case B has the complete fitness function shown in (6). The results are illustrated in Table III. Three new metrics are shown in this test, these are:…”

Section: Impact Of Carpooler Riding Preferencesmentioning

confidence: 99%

“…Another solution is based on the Dijkstra Algorithm [6]. The network of users is subdivided into small areas centered on a driver.…”

Section: Introductionmentioning

confidence: 99%

An intelligent carpooling app for a green social solution to traffic and parking congestions

Dakroub

Boukhater

Lahoud

et al. 2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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Because existing public transportation infrastructure cannot be adapted in a timely manner to address the daunting traffic and parking congestion in urban environments, researchers are investigating social solutions, such as carpooling, where a driver and one or more passengers having semi-common routes share a private vehicle. Although many carpooling systems have been proposed, most of them lack various levels of automation, functionality, practicality, and solution quality. While Genetic Algorithms (GAs) have been successfully adopted for solving combinatorial optimization problems, their use is highly uncommon in carpooling problems. Motivated to propose a solution for the many to many carpooling scenario, we present in this paper a GA with a customized fitness function that searches for the solution with minimal travel distance, efficient ride matching, timely arrival, and maximum fairness while taking into account the riding preferences of the carpoolers. The computational results and simulations based on real user data show the merits of the proposed method and motivate follow up research.

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A distributed dijkstra's algorithm for the implementation of a Real Time Carpooling Service with an optimized aspect on siblings

Cited by 19 publications

References 6 publications

Never drive alone: Boosting carpooling with network analysis

Never drive alone: Boosting carpooling with network analysis

Intelligent Carpooling System

An intelligent carpooling app for a green social solution to traffic and parking congestions

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