Partitioning the time of day for bus schedule optimization

Alperen Bulut; Seda Yanık

doi:10.1007/978-3-030-23756-1_37

Partitioning the time of day for bus schedule optimization

Alperen Bulut, Seda Yanık^*

^*Corresponding author for this work

Department of Industrial Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Time of day partition of bus operating hours is a prerequisite of bus schedule design. Reasonable partition plan is essential to improve the punctuality and level of service. In Istanbul, bus vehicles have been equipped with smart card system. With smart card data passenger boarding time and landing time can be obtained. The number of people between stations in a bus route can be acquired using this boarding and landing time stamps of passengers. In this paper, k-means and fuzzy c-means clustering method will be used and compared to partition the operating day of a bus line in Istanbul into time of day intervals using the bus occupancy rate. Bus occupancy rate will be clustered as low density (very comfortable), normal and overcrowded (disturbing). Membership functions of bus occupancy rates will be based on bus capacity of specified bus route. The resulting clusters could be used in scheduling of bus lines including the frequency and size of buses in different times of day.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
Publisher	Springer Verlag
Pages	298-304
Number of pages	7
ISBN (Print)	9783030237554
DOIs	https://doi.org/10.1007/978-3-030-23756-1_37
Publication status	Published - 2020
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey Duration: 23 Jul 2019 → 25 Jul 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1029
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2019
Country/Territory	Turkey
City	Istanbul
Period	23/07/19 → 25/07/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Bus service measurement
Fuzzy c-means
K-means
Time of day intervals

Access to Document

10.1007/978-3-030-23756-1_37

Cite this

Bulut, A., & Yanık, S. (2020). Partitioning the time of day for bus schedule optimization. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference (pp. 298-304). (Advances in Intelligent Systems and Computing; Vol. 1029). Springer Verlag. https://doi.org/10.1007/978-3-030-23756-1_37

Bulut, Alperen ; Yanık, Seda. / Partitioning the time of day for bus schedule optimization. Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A.Cagri Tolga. Springer Verlag, 2020. pp. 298-304 (Advances in Intelligent Systems and Computing).

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abstract = "Time of day partition of bus operating hours is a prerequisite of bus schedule design. Reasonable partition plan is essential to improve the punctuality and level of service. In Istanbul, bus vehicles have been equipped with smart card system. With smart card data passenger boarding time and landing time can be obtained. The number of people between stations in a bus route can be acquired using this boarding and landing time stamps of passengers. In this paper, k-means and fuzzy c-means clustering method will be used and compared to partition the operating day of a bus line in Istanbul into time of day intervals using the bus occupancy rate. Bus occupancy rate will be clustered as low density (very comfortable), normal and overcrowded (disturbing). Membership functions of bus occupancy rates will be based on bus capacity of specified bus route. The resulting clusters could be used in scheduling of bus lines including the frequency and size of buses in different times of day.",

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Bulut, A & Yanık, S 2020, Partitioning the time of day for bus schedule optimization. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Advances in Intelligent Systems and Computing, vol. 1029, Springer Verlag, pp. 298-304, International Conference on Intelligent and Fuzzy Systems, INFUS 2019, Istanbul, Turkey, 23/07/19. https://doi.org/10.1007/978-3-030-23756-1_37

Partitioning the time of day for bus schedule optimization. / Bulut, Alperen; Yanık, Seda.
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A.Cagri Tolga. Springer Verlag, 2020. p. 298-304 (Advances in Intelligent Systems and Computing; Vol. 1029).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bulut, Alperen

AU - Yanık, Seda

PY - 2020

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N2 - Time of day partition of bus operating hours is a prerequisite of bus schedule design. Reasonable partition plan is essential to improve the punctuality and level of service. In Istanbul, bus vehicles have been equipped with smart card system. With smart card data passenger boarding time and landing time can be obtained. The number of people between stations in a bus route can be acquired using this boarding and landing time stamps of passengers. In this paper, k-means and fuzzy c-means clustering method will be used and compared to partition the operating day of a bus line in Istanbul into time of day intervals using the bus occupancy rate. Bus occupancy rate will be clustered as low density (very comfortable), normal and overcrowded (disturbing). Membership functions of bus occupancy rates will be based on bus capacity of specified bus route. The resulting clusters could be used in scheduling of bus lines including the frequency and size of buses in different times of day.

AB - Time of day partition of bus operating hours is a prerequisite of bus schedule design. Reasonable partition plan is essential to improve the punctuality and level of service. In Istanbul, bus vehicles have been equipped with smart card system. With smart card data passenger boarding time and landing time can be obtained. The number of people between stations in a bus route can be acquired using this boarding and landing time stamps of passengers. In this paper, k-means and fuzzy c-means clustering method will be used and compared to partition the operating day of a bus line in Istanbul into time of day intervals using the bus occupancy rate. Bus occupancy rate will be clustered as low density (very comfortable), normal and overcrowded (disturbing). Membership functions of bus occupancy rates will be based on bus capacity of specified bus route. The resulting clusters could be used in scheduling of bus lines including the frequency and size of buses in different times of day.

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PB - Springer Verlag

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ER -

Bulut A, Yanık S. Partitioning the time of day for bus schedule optimization. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Springer Verlag. 2020. p. 298-304. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-23756-1_37

Partitioning the time of day for bus schedule optimization

Abstract

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Bibliographical note

Keywords

Access to Document

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