A BIBLIOMETRIC ANALYSIS OF ROUTING OPTIMIZATION IN PUBLIC TRANSPORTATION VEHICLES

Abstract

The purpose of this study is to conduct a bibliometric analysis of research focused on the routing of public transportation bus. In accordance with this purpose, a search conducted in the Web of Science database identified 233 publications meeting the specified criteria. Using the VOSviewer software, co-authorship analysis, citation analysis, and keyword analysis were performed on these 233 studies. According to the analysis results, Guan Wei was identified as the most productive author in the field of public transportation vehicle routing and China was being the leading country in terms of publication volume. The most frequently used keyword was determined to be "routing". Additionally, the journal with the highest number of publications in this field was “Transportation Research Part C: Emerging Technologies,” while the most cited study was authored by Tong, Zhou, Liu, and Zhou (2017), receiving a total of 157 citations.

Keywords

• Vehicle Routing
• Public Transportation
• Bibliometric Analysis

TOPLU TAŞIMA ARAÇLARININ ROTALAMA OPTİMİZASYONUNUN BİBLİYOMETRİK ANALİZİ

Abstract

Bu çalışmanın amacı toplu taşıma otobüsleri için rotalama yapan çalışmaların bibliyometrik analizini yapmaktır. Bu amaç doğrultusunda Web of Science veri tabanında yapılan araştırma sonucunda istenilen kriterlere sahip 233 tane yayına ulaşılmıştır. VOSviwer programı kullanılarak bu 233 çalışmaya ortak yazarlık analizi, atıf analizi ve anahtar kelime analizi yapılmıştır. Analiz sonuçlarına göre toplu taşıma araçlarının rotalanması ile ilgili en çok yayın yapan yazarın Guan Wei olduğu, en çok Çin Halk Cumhuriyeti’nin yayın yapıldığı ve en çok kullanılan anahtar kelimenin routing yani rotalama olduğu belirlenmiştir. En çok yayın yapılan derginin “Transportation Research Part C-Emerging Technologies” olduğu ve en çok atıf alan yayının ise Tong, Zhou, Liu ve Zhou (2017) tarafından yapıldığı ve çalışmanın toplamda 157 atıf aldığı tespit edilmiştir.

Keywords

• Araç Rotalama
• Toplu Taşıma
• Bibliyometrik Analiz

References

1. Ahmed, L., Mumford, C., & Kheiri, A. (2019). Solving urban transit route design problem using selection hyper-heuristics. European Journal of Operational Research, 274(2), 545-559. https://doi.org/10.1016/j.ejor.2018.10.022
2. Basso, R., Kulcsár, B., Egardt, B., Lindroth, P., & Sanchez-Diaz, I. (2019). Energy consumption estimation integrated into the electric vehicle routing problem. Transportation research part d: Transport and environment, 69, 141-167. https://doi.org/10.1016/j.trd.2019.01.006
3. Boz, E. Y., & Aras, F. (2021). Yeşil araç rotalama problemi araştırması: geçmiş ve gelecekteki eğilimler. Journal of Turkish Operations Management, 5(2), 806-821.
4. Ceder, A., & Wilson, N. H. (1986). Bus network design. Transportation Research Part B: Methodological, 20(4), 331-344. https://doi.org/10.1016/0191-2615(86)90047-0
5. Ceder, A., & Israeli, Y. (1993, September). Design and evaluation of transit routes in urban networks. In Proceedings of the 3rd international conference on competition and ownership in surface passenger transport, Ontario, Canada.
6. Ceder, A., & Israeli, Y. (1997). Creation of Objective functions for transit network design. IFAC Proceedings Volumes, 30(8), 667-673. https://doi.org/10.1016/S1474-6670(17)43897-3
7. Ceder, A., & Israeli, Y. (1998). User and operator perspectives in transit network design. Transportation Research Record, 1623(1), 3-7. https://doi.org/10.3141/1623-01
8. Ceder, A. (2001). Operational objective functions in designing public transport routes. Journal of advanced transportation, 35(2), 125-144. https://doi.org/10.1002/atr.5670350205

9. Ceder, A. (2007). Public transit planning and operation: Theory, modelling and practice. CRC Press.
10. Chakroborty, P., & Wivedi, T. (2002). Optimal route network design for transit systems using genetic algorithms. Engineering optimization, 34(1), 83-100. https://doi.org/10.1080/03052150210909
11. Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management science, 6(1), 80-91. https://doi.org/10.1287/mnsc.6.1.80
12. Delling, D., Pajor, T., & Werneck, R. F. (2015). Round-based public transit routing. Transportation Science, 49(3), https://doi.org/10.1287/trsc.2014.0534
13. Demirbilek, M. (2023). A bibliometric analysis of publications related to dynamic vehicle routing problems. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 6(2), 267-283, https://doi.org/10.51513/jitsa.1230420
14. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
15. European Committee for Standardization. (2002). Transportation - logistics and services - public passenger transport - service quality definition, targeting and measurement. CEN-EN 13816, CEN.
16. Guihaire, V., & Hao, J. K. (2008). Transit network design and scheduling: A global review. Transportation Research Part A: Policy and Practice, 42(10), 1251-1273. https://doi.org/10.1016/j.tra.2008.03.011
17. Gürgen, E., & Wong, C. Y. (2016, December). Networks of research collaboration in logistics and supply chain management: the case of Turkey. In LM-SCM 2016 XIV. International Logistics and Supply Chain Congress. 151- 166.
18. He, D., Ceder, A. A., Zhang, W., Guan, W., & Qi, G. (2023). Optimization of a rural bus service integrated with e-commerce deliveries guided by a new sustainable policy in China. Transportation Research Part E: Logistics and Transportation Review, 172, 103069. https://doi.org/10.1016/j.tre.2023.103069
19. Huang, D., Gu, Y., Wang, S., Liu, Z., & Zhang, W. (2020). A two-phase optimization model for the demand-responsive customized bus network design. Transportation research part c: emerging technologies, 111, 1-21. https://doi.org/10.1016/j.trc.2019.12.004
20. Iliopoulou, C., Kepaptsoglou, K., & Vlahogianni, E. (2019). Metaheuristics for the transit route network design problem: a review and comparative analysis. Public Transport, 11, 487-521. https://doi.org/10.1007/s12469-019-00211-2
21. Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de la Información, 29(1). 1-20. https://doi.org/10.3145/epi.2020.ene.03
22. Kechagiopoulos, P. N., & Beligiannis, G. N. (2014). Solving the urban transit routing problem using a particle swarm optimization based algorithm. Applied Soft Computing, 21, 654-676. https://doi.org/10.1016/j.asoc.2014.04.005
23. Li, H., Zhou, J., & Xu, K. (2023). Evolution of green vehicle routing problem: A bibliometric and visualized review. Sustainability, 15(23), 16149, https://doi.org/10.3390/su152316149
24. Lin, Y., Zhang, K., Shen, Z. J. M., Ye, B., & Miao, L. (2019). Multistage large-scale charging station planning for electric buses considering transportation network and power grid. Transportation Research Part C: Emerging Technologies, 107, 423-443. https://doi.org/10.1016/j.trc.2019.08.009
25. Lyu, Y., Chow, C. Y., Lee, V. C., Ng, J. K., Li, Y., & Zeng, J. (2019). CB-Planner: A bus line planning framework for customized bus systems. Transportation Research Part C: Emerging Technologies, 101, 233-253. https://doi.org/10.1016/j.trc.2019.02.006
26. Marin, A., & Wellman, B. (2011). Social network analysis: An introduction. The SAGE handbook of social network analysis, 11, 25.
27. Merigó, J. M., & Yang, J. B. (2017). A bibliometric analysis of operations research and management science. Omega, 73, 37-48. https://doi.org/10.1016/j.omega.2016.12.004
28. Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de la Información, 29(1), https://doi.org/10.3145/epi.2020.ene.03
29. OECD, I. (2010). Reducing transport greenhouse gas emissions: Trends and data 2010. https://www.itf-oecd.org/reducing-transport-greenhouse-gas-emissions-trends-and-data-2010
30. Owais, M., & Osman, M. K. (2018). Complete hierarchical multi-objective genetic algorithm for transit network design problem. Expert Systems with Applications, 114, 143-154. https://doi.org/10.1016/j.eswa.2018.07.033
31. Shrivastava, P., & O’Mahony, M. (2006). A model for development of optimized feeder routes and coordinated schedules—A genetic algorithms approach. Transport policy, 13(5), 413-425. https://doi.org/10.1016/j.tranpol.2006.03.002
32. Tong, L. C., Zhou, L., Liu, J., & Zhou, X. (2017). Customized bus service design for jointly optimizing passenger-to-vehicle assignment and vehicle routing. Transportation research part c: emerging technologies, 85, 451-475. https://doi.org/10.1016/j.trc.2017.09.022
33. Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538, https://doi.org/10.1007/s11192-009-0146-3
34. Van Eck, N. J. V., Waltman, L., van den Berg, J., & Kaymak, U. (2006). Visualizing the computational intelligence field [application notes]. IEEE Computational Intelligence Magazine, 1(4), 6-10.
35. Wasserman, S. (1994). Social network analysis: Methods and applications. The Press Syndicate of the University of Cambridge.