國立虎尾科技大學 |

Designing Feeder Bus Routes by Using Smart Card Data = = Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Designing Feeder Bus Routes by Using Smart Card Data =/
Reminder of title:	Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.
remainder title:	Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.
Author:	Abdulrahman, Hassan Shuaibu.
Description:	1 online resource (157 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-08, Section: B.
Contained By:	Dissertations Abstracts International85-08B.
Subject:	Socioeconomic factors. -
Online resource:	click for full text (PQDT)
ISBN:	9798381583465

Designing Feeder Bus Routes by Using Smart Card Data = = Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.
Abdulrahman, Hassan Shuaibu.

Designing Feeder Bus Routes by Using Smart Card Data =Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi. - 1 online resource (157 pages)

Source: Dissertations Abstracts International, Volume: 85-08, Section: B.

Thesis (Ph.D.)--Dokuz Eylul Universitesi (Turkey), 2021.

Includes bibliographical references

Attempts have been made of over decades to design a more efficient and yet sustainable transportation system by using different mass transportation systems. A simple form of this, is the intermodal transportation system which can be described by feeder bus route design problem (FBRNDP). One of the fundamental components of transit planning is the estimation of origin-destination (O-D) matrix. Collecting such data, however, is extremely difficult and expensive using traditional paper-surveybased approaches which are rarely available. Therefore, a new data source was explored in the form of transit smart cards. This spatio-temporal data is most important for any meaningful transit smart card studies, and even so, if they are used alongside other data sources such as data base management system and geographic information systems, their potential can be harnessed. Multiple Traveling Salesman Problem (MTSP) is similar to FBRNDP in which there are many origins and one destination. The main purpose of this research is to develop a methodology for the planning of public feeder bus routes by using smart card data, transit network with existing bus stop coordinates and a distance optimization algorithm. In this study, important aspects of feeder bus route network design are highlighted, a method for the determining of potential feeder bus stop location developed, and a modified genetic algorithm was used to solve FBRNDP. The methodology was used to design a new feeder bus routes, and the best solution was selected via pareto efficiency and minimized total system cost.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381583465Subjects--Topical Terms:

1437659
Socioeconomic factors.
Index Terms--Genre/Form:

554714
Electronic books.

Designing Feeder Bus Routes by Using Smart Card Data = = Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.
LDR:03110ntm a22004097 4500 001 1147349
005 20240909100804.5
006 m o d
007 cr bn ---uuuuu
008 250605s2021 xx obm 000 0 eng d
020 $a 9798381583465
035 $a (MiAaPQ)AAI30834269
035 $a (MiAaPQ)DokuzEyluld5cc090770de4bab891b31314def049a
035 $a AAI30834269
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Abdulrahman, Hassan Shuaibu. $3 1473055
245 1 0 $a Designing Feeder Bus Routes by Using Smart Card Data = $b Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.
246 3 1 $a Otobus Besleme Guzergahlarinin Akilli Kart Verileri Kullanilarak Tasarlanmasi.
264 0 $c 2021
300 $a 1 online resource (157 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-08, Section: B.
500 $a Advisor: Ozuysal, Mustafa.
502 $a Thesis (Ph.D.)--Dokuz Eylul Universitesi (Turkey), 2021.
504 $a Includes bibliographical references
520 $a Attempts have been made of over decades to design a more efficient and yet sustainable transportation system by using different mass transportation systems. A simple form of this, is the intermodal transportation system which can be described by feeder bus route design problem (FBRNDP). One of the fundamental components of transit planning is the estimation of origin-destination (O-D) matrix. Collecting such data, however, is extremely difficult and expensive using traditional paper-surveybased approaches which are rarely available. Therefore, a new data source was explored in the form of transit smart cards. This spatio-temporal data is most important for any meaningful transit smart card studies, and even so, if they are used alongside other data sources such as data base management system and geographic information systems, their potential can be harnessed. Multiple Traveling Salesman Problem (MTSP) is similar to FBRNDP in which there are many origins and one destination. The main purpose of this research is to develop a methodology for the planning of public feeder bus routes by using smart card data, transit network with existing bus stop coordinates and a distance optimization algorithm. In this study, important aspects of feeder bus route network design are highlighted, a method for the determining of potential feeder bus stop location developed, and a modified genetic algorithm was used to solve FBRNDP. The methodology was used to design a new feeder bus routes, and the best solution was selected via pareto efficiency and minimized total system cost.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Socioeconomic factors. $3 1437659
650 4 $a Public transportation. $3 1467920
650 4 $a Buses. $3 721324
650 4 $a Clustering. $3 1413637
650 4 $a Vehicles. $3 721652
650 4 $a Scheduling. $3 719495
650 4 $a Sensitivity analysis. $3 1465552
650 4 $a Planning. $3 660157
650 4 $a Genetic algorithms. $3 655041
650 4 $a Design. $3 595500
650 4 $a Geographic information systems. $3 554796
650 4 $a Neighborhoods. $3 888883
650 4 $a Cities. $3 1413482
650 4 $a Passengers. $3 1473056
650 4 $a Geographic information science. $3 1372545
650 4 $a Information technology. $3 559429
650 4 $a Sociology. $3 551705
650 4 $a Transportation. $3 558117
655 7 $a Electronic books. $2 local $3 554714
690 $a 0389
690 $a 0800
690 $a 0501
690 $a 0370
690 $a 0489
690 $a 0626
690 $a 0709
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Dokuz Eylul Universitesi (Turkey). $3 1466111
773 0 $t Dissertations Abstracts International $g 85-08B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30834269 $z click for full text (PQDT)