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Determining Bus Stops to be Equipped with Charging Devices for Electric Buses Using the Binary Genetic Algorithm

Year 2025, Volume: 25 Issue: 6, 1427 - 1438

Abstract

In recent years, the efficient use of public transport systems has emerged as an effective solution to the rapidly increasing transport-based problems. Despite being a relatively sustainable transportation mode compared to other modes, diesel-powered buses, which constitute the majority of public transport vehicles, are responsible for a significant proportion of transport-related emissions. As a result, electric buses are seen as a promising option for sustainable urban public transport systems. However, due to their limited driving range, electric buses may experience service disruptions throughout the day as their energy levels decrease. This study develops an optimization model that enables electric buses to meet their daily energy requirements by wirelessly charging at selected stops during passenger boarding and alighting times within the transit network. The stops to be equipped with charging devices are determined using a Binary Genetic Algorithm, under operational constraints that ensure uninterrupted service of electric buses throughout the day, with the objective of minimizing the total investment cost. An analysis of the results obtained from the developed optimization model reveals that the Binary Genetic Algorithm achieves the best solution in significantly shorter computation times and with high reliability, when compared to the exact solution obtained using the Branch and Bound method.

References

  • Aksoy, İ.C., Mutlu, M.M. and Alver Y., (2024). Addressing charging infrastructure location problem considering a dynamic and supply. CETRA 2024. Catvat, Croatia, 381-388.
  • Ameer, H., Wang, Y. and Chen, Z., 2025. A density-based spatial clustering and linear programming method for electric vehicle charging station location and price optimization. Energy, 317, 134581. https://doi.org/10.1016/j.energy.2025.134581
  • Arbex, R.O. and da Cunha C.B., 2015. Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm. Transportation Research Part B, 81, 355-376, 2015. https://doi.org/10.1016/j.trb.2015.06.014
  • Bilgilioğlu, S.S., 2022. Coğrafi Bilgi Sistemleri ve Bulanık Analitik Hiyerarşi Süreci ile Elektrikli Araç Şarj İstasyonu Yer Seçimi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 22(1), 165 - 174. https://doi.org/10.35414/akufemubid.1013244
  • Calvo-Jurado, C., Ceballos-Martínez, J.M., García-Merino, J.C., Muñoz-Solano, M. and Sánchez-Herrera, F.J., 2015. Optimal location of electric vehicle charging stations using proximity diagrams. Sustainable Cities and Society, 113, 105719, 2024. https://doi.org/10.1016/j.scs.2024.105719
  • Ceder, A., 2007. Public Transit Planning and Operation: Modeling, Practice and Behavior, Butterworth-Heinemann.
  • Farahani, R. Z., Miandoabchi, E., Szeto, W.Y. and Rashidi, H., 2013. A review of urban transportation network design problems. European Journal of Operational Research, 229(2), 281–302. https://doi.org/10.1016/j.ejor.2013.01.001
  • Gao, Z., LaClair, T., Daw, C., Smith, D. and Franzese, O., 2014. Simulations of the fuel economy and emissions of hybrid transit buses over planned local routes. SAE International Journal of Commercial Vehicles, 7(1), 216-237. https://doi.org/10.4271/2014-01-1562
  • Gao, Z., Lin, Z., LaClair, T., Liu, C., Li, J., Birky, A. and Ward, J., 2017. Battery capacity and recharging needs for electric buses in city transit service. Energy, 122, 588-600. https://doi.org/10.1016/j.energy.2017.01.101
  • Göhlich, D., Fay, T., Jefferies, D., Lauth, E., Kunith, A. and Zhang, X., 2018. Design of urban electric bus systems, Design Science, 4, e15. https://doi.org/10.1017/dsj.2018.10
  • Herrera, F., Lozano, M. and Verdegay, J.T., 1998. Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis. Artificial Intelligence Review, 12, 265–319. https://doi.org/10.1023/A:1006504901164
  • Illiopolou, C. and Kepaptsoglou, K., 2019. Integrated transit route network design and infrastructure planning for on-line electric vehicles. Transportation Research Part D, 77, 178- 197. https://doi.org/10.1016/j.trd.2019.10.016
  • Illiopolou, C., Tassopoulos, I., Kepaptsoglou, K., Beligiannis G., 2019. Electric Transit Route Network Design Problem: Model and Application. Transportation Research Record, 2673(8), 275-283. https://doi.org/10.1177/0361198119838513
  • Katoch, S., Chauhan, S.S. and Kumar, V., 2021. A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80, 8091-8126. https://doi.org/10.1007/s11042-020-10139-6
  • Kunith, A., Mendelevitch, R. and Göehlich, D., 2017. Electrification of a city bus network—An optimization model for cost-effective placing of charging infrastructure and battery sizing of fast-charging electric bus systems. International Journal of Sustainable Transportation, 11(10), 707-720. https://doi.org/10.1080/15568318.2017.1310962
  • Kunith, A., Mendelevitch, R., Kuschmierz, A. and Göehlich D., (2016). Optimization of fast charging infrastructure for electric bus transportation – Electrification of a city bus network. EVS29 Symposium. Montreal, Canada, 438-449.
  • Lin, Y., Zhang, K., Shen, Z.M., Ye, B. and Miao, L., 2019. Multistage large-scale charging station planning for electric buses considering transportation network and power grid. Transportation Research Part C, 107, 423-443. https://doi.org/10.1016/j.trc.2019.08.009
  • Liu, Y., Feng, X., Ding, C., Hua, Q. and Ruan, Z., 2020. Electric Transit Network Design by an Improved Artificial Fish-Swarm Algorithm. Journal of Transportation Engineering Part A: Systems, 146(8), 0402007. https://doi.org/10.1061/JTEPBS.0000393
  • Liu, Y., Feng, X., Yang, Y., Ruan, Z. and Li, K., 2022. Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm. Journal of Intelligent Transportation Systems, (26)3, 253-268. https://doi.org/10.1080/15472450.2020.1848561
  • Liu, Y., Feng, X., Zhang, L., Hua, Q. and Li, K., 2020. A pareto artificial fish swarm algorithm for solving a multi-objective electric transit network design problem. Transportmetrica A: Transport Science, 16(3), 1648-1670. https://doi.org/10.1080/23249935.2020.1773574
  • Magnanti, T.L. and Wong, R.T., 1984. Network Design and Transportation Planning: Models and Algorithms. Transportation Science, 18(1), 1–55. https://doi.org/10.1287/trsc.18.1.1
  • Mposdra, A., Iliopoulou, C., Kepaptsoglou, K., Vlahogianni, E. and Tyrinopoulos, Y., 2018. Rapid transit network design for on-line electric vehicles. Advances in Transportation Studies: an International Journal Section, 46, 19-30. https://doi.org/10.4399/9788255186412
  • Noel, L. and McCormack, R., 2014. A cost benefit analysis of a V2G-capable electric school bus compared to a traditional diesel school bus. Applied Energy, 126, 246-255. https://doi.org/10.1016/j.apenergy.2014.04.009
  • Uslu, T. and Kara, O., 2021. Location and capacity decisions for electric bus charging stations considering waiting times. Transportation Research Part D: Transport and Environment, 90, 102645. https://doi.org/10.1016/j.trd.2020.102645
  • Wang, X., Yuen, C., Hassan, N., An, N. and Wu, W., 2017. Electric Vehicle Charging Station Placement for Urban Public Bus Systems. IEEE Trannsactions on Intellegent Transportation Sysstems, 18, 128-139. https://doi.org/10.1109/TITS.2016.2563166
  • Yang, X., Niu, D., Sun, L., Ji, Z., Zhou, J., Wang, K. and Siqin, Z., 2021. A bi-level optimization model for electric vehicle charging strategy based on regional grid load following. Journal of Cleaner Production, 325, 129313. https://doi.org/10.1016/j.jclepro.2021.129313
  • Yang, X.S., 2010. Engineering Optimization. John Wiley & Sons. Yomralıoğlu, T. and Güler, D., 2020. Açık Kaynak Kodlu CBS Yazılımı ve Bulanık Analitik Hiyerarşi Yöntemini İçeren Elektrikli Araç Şarj İstasyonu Yer Seçimi Önerisi. Harita Dergisi, (86)163, 17-28.
  • Sustainable Bus Editorial Board, Electric bus range, focus on electricity consumption. A sum-up, https://www.sustainable-bus.com/news/electric-bus-range-electricity-consumption, (12.12.2024)

Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi

Year 2025, Volume: 25 Issue: 6, 1427 - 1438

Abstract

Toplu taşıma sistemlerinin etkin kullanımı son yıllarda hızla artan ulaşım tabanlı problemlere karşı etkili bir çözüm yolu olarak görülmektedir. Toplu taşıma diğer ulaşım türlerine kıyasla sürdürülebilir bir ulaşım türü olsa da ulaşım kaynaklı emisyonun önemli bir oranına toplu taşıma taşıtlarının çoğunluğunu oluşturan dizel motora sahip otobüsler yol açmaktadır. Bu nedenle, kentsel ulaşımda sürdürülebilir bir toplu taşıma sistemi tesis etmek için elektrikli otobüsler tercih edilebilecek seçenekler arasında görülmektedir. Ancak, sınırlı menzile sahip elektrikli otobüsler, gün içinde enerji seviyelerinin düşmesi nedeniyle hizmet dışı kalabilmektedir. Bu çalışmada, toplu taşıma ağlarında belirli duraklara kablosuz şarj cihazları yerleştirerek, elektrikli otobüslerin yolcu indirme/bindirme süreleri boyunca gün boyunca ihtiyaç duydukları enerjiyi temin etmelerini sağlayan bir optimizasyon modeli geliştirilmiştir. Şarj cihazı ile donatılacak duraklar, yatırım maliyetinin minimizasyonu amacıyla ve elektrikli otobüslerin hizmetlerine gün boyunca herhangi bir aksama yaşamadan devam edebilmesini sağlayan kısıtlar altında, İkili Genetik Algoritma kullanılarak belirlenmektedir. Geliştirilen optimizasyon modelinden elde edilen sonuçlar incelendiğinde İkili Genetik Algoritma’nın, Dal Sınır Yöntemi ile elde edilen kesin çözüm ile karşılaştırıldığında, çok daha kısa sürelerde ve yüksek güvenilirlikle en iyi çözüme ulaşabildiği görülmektedir.

Ethical Statement

Bu çalışmanın hazırlanma sürecinde bilimsel ve etik ilkelere uyulduğu ve yararlanılan tüm çalışmaların kaynakçada belirtildiği beyan olunur. Bu çalışma Prof. Dr. Yalçın ALVER danışmanlığında İlyas Cihan AKSOY tarafından 01/12/2023 tarihinde tamamlanan “Elektrikli otobüsler için çok amaçlı toplu taşıma ağ tasarımı” başlıklı doktora (Tez no: 843747) tezinden türetilmiştir.

References

  • Aksoy, İ.C., Mutlu, M.M. and Alver Y., (2024). Addressing charging infrastructure location problem considering a dynamic and supply. CETRA 2024. Catvat, Croatia, 381-388.
  • Ameer, H., Wang, Y. and Chen, Z., 2025. A density-based spatial clustering and linear programming method for electric vehicle charging station location and price optimization. Energy, 317, 134581. https://doi.org/10.1016/j.energy.2025.134581
  • Arbex, R.O. and da Cunha C.B., 2015. Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm. Transportation Research Part B, 81, 355-376, 2015. https://doi.org/10.1016/j.trb.2015.06.014
  • Bilgilioğlu, S.S., 2022. Coğrafi Bilgi Sistemleri ve Bulanık Analitik Hiyerarşi Süreci ile Elektrikli Araç Şarj İstasyonu Yer Seçimi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 22(1), 165 - 174. https://doi.org/10.35414/akufemubid.1013244
  • Calvo-Jurado, C., Ceballos-Martínez, J.M., García-Merino, J.C., Muñoz-Solano, M. and Sánchez-Herrera, F.J., 2015. Optimal location of electric vehicle charging stations using proximity diagrams. Sustainable Cities and Society, 113, 105719, 2024. https://doi.org/10.1016/j.scs.2024.105719
  • Ceder, A., 2007. Public Transit Planning and Operation: Modeling, Practice and Behavior, Butterworth-Heinemann.
  • Farahani, R. Z., Miandoabchi, E., Szeto, W.Y. and Rashidi, H., 2013. A review of urban transportation network design problems. European Journal of Operational Research, 229(2), 281–302. https://doi.org/10.1016/j.ejor.2013.01.001
  • Gao, Z., LaClair, T., Daw, C., Smith, D. and Franzese, O., 2014. Simulations of the fuel economy and emissions of hybrid transit buses over planned local routes. SAE International Journal of Commercial Vehicles, 7(1), 216-237. https://doi.org/10.4271/2014-01-1562
  • Gao, Z., Lin, Z., LaClair, T., Liu, C., Li, J., Birky, A. and Ward, J., 2017. Battery capacity and recharging needs for electric buses in city transit service. Energy, 122, 588-600. https://doi.org/10.1016/j.energy.2017.01.101
  • Göhlich, D., Fay, T., Jefferies, D., Lauth, E., Kunith, A. and Zhang, X., 2018. Design of urban electric bus systems, Design Science, 4, e15. https://doi.org/10.1017/dsj.2018.10
  • Herrera, F., Lozano, M. and Verdegay, J.T., 1998. Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis. Artificial Intelligence Review, 12, 265–319. https://doi.org/10.1023/A:1006504901164
  • Illiopolou, C. and Kepaptsoglou, K., 2019. Integrated transit route network design and infrastructure planning for on-line electric vehicles. Transportation Research Part D, 77, 178- 197. https://doi.org/10.1016/j.trd.2019.10.016
  • Illiopolou, C., Tassopoulos, I., Kepaptsoglou, K., Beligiannis G., 2019. Electric Transit Route Network Design Problem: Model and Application. Transportation Research Record, 2673(8), 275-283. https://doi.org/10.1177/0361198119838513
  • Katoch, S., Chauhan, S.S. and Kumar, V., 2021. A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80, 8091-8126. https://doi.org/10.1007/s11042-020-10139-6
  • Kunith, A., Mendelevitch, R. and Göehlich, D., 2017. Electrification of a city bus network—An optimization model for cost-effective placing of charging infrastructure and battery sizing of fast-charging electric bus systems. International Journal of Sustainable Transportation, 11(10), 707-720. https://doi.org/10.1080/15568318.2017.1310962
  • Kunith, A., Mendelevitch, R., Kuschmierz, A. and Göehlich D., (2016). Optimization of fast charging infrastructure for electric bus transportation – Electrification of a city bus network. EVS29 Symposium. Montreal, Canada, 438-449.
  • Lin, Y., Zhang, K., Shen, Z.M., Ye, B. and Miao, L., 2019. Multistage large-scale charging station planning for electric buses considering transportation network and power grid. Transportation Research Part C, 107, 423-443. https://doi.org/10.1016/j.trc.2019.08.009
  • Liu, Y., Feng, X., Ding, C., Hua, Q. and Ruan, Z., 2020. Electric Transit Network Design by an Improved Artificial Fish-Swarm Algorithm. Journal of Transportation Engineering Part A: Systems, 146(8), 0402007. https://doi.org/10.1061/JTEPBS.0000393
  • Liu, Y., Feng, X., Yang, Y., Ruan, Z. and Li, K., 2022. Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm. Journal of Intelligent Transportation Systems, (26)3, 253-268. https://doi.org/10.1080/15472450.2020.1848561
  • Liu, Y., Feng, X., Zhang, L., Hua, Q. and Li, K., 2020. A pareto artificial fish swarm algorithm for solving a multi-objective electric transit network design problem. Transportmetrica A: Transport Science, 16(3), 1648-1670. https://doi.org/10.1080/23249935.2020.1773574
  • Magnanti, T.L. and Wong, R.T., 1984. Network Design and Transportation Planning: Models and Algorithms. Transportation Science, 18(1), 1–55. https://doi.org/10.1287/trsc.18.1.1
  • Mposdra, A., Iliopoulou, C., Kepaptsoglou, K., Vlahogianni, E. and Tyrinopoulos, Y., 2018. Rapid transit network design for on-line electric vehicles. Advances in Transportation Studies: an International Journal Section, 46, 19-30. https://doi.org/10.4399/9788255186412
  • Noel, L. and McCormack, R., 2014. A cost benefit analysis of a V2G-capable electric school bus compared to a traditional diesel school bus. Applied Energy, 126, 246-255. https://doi.org/10.1016/j.apenergy.2014.04.009
  • Uslu, T. and Kara, O., 2021. Location and capacity decisions for electric bus charging stations considering waiting times. Transportation Research Part D: Transport and Environment, 90, 102645. https://doi.org/10.1016/j.trd.2020.102645
  • Wang, X., Yuen, C., Hassan, N., An, N. and Wu, W., 2017. Electric Vehicle Charging Station Placement for Urban Public Bus Systems. IEEE Trannsactions on Intellegent Transportation Sysstems, 18, 128-139. https://doi.org/10.1109/TITS.2016.2563166
  • Yang, X., Niu, D., Sun, L., Ji, Z., Zhou, J., Wang, K. and Siqin, Z., 2021. A bi-level optimization model for electric vehicle charging strategy based on regional grid load following. Journal of Cleaner Production, 325, 129313. https://doi.org/10.1016/j.jclepro.2021.129313
  • Yang, X.S., 2010. Engineering Optimization. John Wiley & Sons. Yomralıoğlu, T. and Güler, D., 2020. Açık Kaynak Kodlu CBS Yazılımı ve Bulanık Analitik Hiyerarşi Yöntemini İçeren Elektrikli Araç Şarj İstasyonu Yer Seçimi Önerisi. Harita Dergisi, (86)163, 17-28.
  • Sustainable Bus Editorial Board, Electric bus range, focus on electricity consumption. A sum-up, https://www.sustainable-bus.com/news/electric-bus-range-electricity-consumption, (12.12.2024)
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Transportation Engineering
Journal Section Articles
Authors

İlyas Cihan Aksoy 0000-0002-4256-8222

Mehmet Metin Mutlu 0000-0003-0008-8279

Yalçın Alver 0000-0002-9833-4505

Early Pub Date November 13, 2025
Publication Date November 14, 2025
Submission Date December 13, 2024
Acceptance Date June 15, 2025
Published in Issue Year 2025 Volume: 25 Issue: 6

Cite

APA Aksoy, İ. C., Mutlu, M. M., & Alver, Y. (2025). Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 25(6), 1427-1438.
AMA Aksoy İC, Mutlu MM, Alver Y. Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. November 2025;25(6):1427-1438.
Chicago Aksoy, İlyas Cihan, Mehmet Metin Mutlu, and Yalçın Alver. “Elektrikli Otobüsler Için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 25, no. 6 (November 2025): 1427-38.
EndNote Aksoy İC, Mutlu MM, Alver Y (November 1, 2025) Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 25 6 1427–1438.
IEEE İ. C. Aksoy, M. M. Mutlu, and Y. Alver, “Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi”, Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 25, no. 6, pp. 1427–1438, 2025.
ISNAD Aksoy, İlyas Cihan et al. “Elektrikli Otobüsler Için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 25/6 (November2025), 1427-1438.
JAMA Aksoy İC, Mutlu MM, Alver Y. Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2025;25:1427–1438.
MLA Aksoy, İlyas Cihan et al. “Elektrikli Otobüsler Için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 25, no. 6, 2025, pp. 1427-38.
Vancouver Aksoy İC, Mutlu MM, Alver Y. Elektrikli Otobüsler için Şarj İstasyonlu Durakların İkili Genetik Algoritma Kullanılarak Belirlenmesi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2025;25(6):1427-38.