Application of a Seat-based Booking Control Mechanism in Rail Transport with Customer Diversion
Received: 1 July 2022 | Accepted: 10 July 2022 | Online: 2 October 2022
Corresponding author: A. Z. Bulum
The ticket booking control mechanism is a part of the Revenue Management (RM), commonly used in the airline industry. This study aims to optimize seat allocation in the railway industry and compare the performance of three booking control techniques by considering customer behavior. The preferences of customers who cannot find their desired ticket are considered as a customer diversion matrix, which also includes waiting and no-purchase probability. Α Ticket Booking System (TBS) with buckets, which assigns seats to buckets, was adapted and implemented on the Turkish railway for the first time. A genetic algorithm that is specifically written to apply the TBS, including customer diversion, is used in simulations to obtain approximate solutions. It is seen that TBS gave successful results with a revenue increase of around 5.8%. We can also suggest, considering customer behavior, that the revenue can be raised by sales in periods.
Keywords:revenue management, railway transportation, genetic algorithm, seat inventory control, customer behavior
J. I. McGill and G. J. van Ryzin, "Revenue Management: Research Overview and Prospects," Transportation Science, vol. 33, no. 2, pp. 233–256, May 1999. DOI: https://doi.org/10.1287/trsc.33.2.233
R. Phillips, Pricing and Revenue Optimization. Stanford, CA, USA: Stanford Business Books, 2005. DOI: https://doi.org/10.1515/9780804781640
S. L. Brumelle and J. I. McGill, "Airline Seat Allocation with Multiple Nested Fare Classes," Operations Research, vol. 41, no. 1, pp. 127–137, Feb. 1993. DOI: https://doi.org/10.1287/opre.41.1.127
R. E. Curry, "Optimal Airline Seat Allocation with Fare Classes Nested by Origins and Destinations," Transportation Science, vol. 24, no. 3, pp. 193–204, Aug. 1990. DOI: https://doi.org/10.1287/trsc.24.3.193
A. Ciancimino, G. Inzerillo, S. Lucidi, and L. Palagi, "A Mathematical Programming Approach for the Solution of the Railway Yield Management Problem," Transportation Science, vol. 33, no. 2, pp. 168–181, May 1999. DOI: https://doi.org/10.1287/trsc.33.2.168
H. Luo, L. Nie, and Z. He, "Modeling of multi-train seat inventory control based on revenue management," in International Conference on Logistics, Informatics and Service Sciences, Sydney, NSW, Australia, Jul. 2016, pp. 1–6. DOI: https://doi.org/10.1109/LISS.2016.7854371
Z. Xie, W. Zhu, and L. Zheng, "A Dynamic Railway Seat Allocation Problem," in Industrial and Systems Engineering Research Conference, Puerto Rico, PR, USA, Dec. 2013, pp. 3480–3489.
Y. Bao, J. Liu, M. Ma, and L. Meng, "Seat inventory control methods for Chinese passenger railways," Journal of Central South University, vol. 21, no. 4, pp. 1672–1682, Apr. 2014. DOI: https://doi.org/10.1007/s11771-014-2109-y
P. Hetrakul and C. Cirillo, "A latent class choice based model system for railway optimal pricing and seat allocation," Transportation Research Part E: Logistics and Transportation Review, vol. 61, pp. 68–83, Jan. 2014. DOI: https://doi.org/10.1016/j.tre.2013.10.005
A. Armstrong and J. Meissner, "Railway Revenue Management: Overview and Models," 2010. https://eprints.lancs.ac.uk/id/eprint/49017.
W. Yuan and L. Nie, "Optimization of seat allocation with fixed prices: An application of railway revenue management in China," PLOS ONE, vol. 15, no. 4, Apr. 2020, Art. no. e0231706. DOI: https://doi.org/10.1371/journal.pone.0231706
C. Cizaire and P. Belobaba, "Joint optimization of airline pricing and fare class seat allocation," Journal of Revenue and Pricing Management, vol. 12, no. 1, pp. 83–93, Jan. 2013. DOI: https://doi.org/10.1057/rpm.2012.27
G. Dutta and D. P. Marodia, "Comparison of forecasting techniques in revenue management for a national railway in an emerging Asian economy," International Journal of Revenue Management, vol. 8, no. 2, pp. 130–152, Jan. 2015. DOI: https://doi.org/10.1504/IJRM.2015.070000
X. Wang, H. Wang, and X. Zhang, "Stochastic seat allocation models for passenger rail transportation under customer choice," Transportation Research Part E: Logistics and Transportation Review, vol. 96, pp. 95–112, Dec. 2016. DOI: https://doi.org/10.1016/j.tre.2016.10.003
H. Jafarzadeh, N. Moradinasab, and M. Elyasi, "An Enhanced Genetic Algorithm for the Generalized Traveling Salesman Problem," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2260–2265, Dec. 2017. DOI: https://doi.org/10.48084/etasr.1570
T. Kara and M. C. Savas, "Design and Simulation of a Decentralized Railway Traffic Control System," Engineering, Technology & Applied Science Research, vol. 6, no. 2, pp. 945–951, Apr. 2016. DOI: https://doi.org/10.48084/etasr.631
J. Zheng, J. Liu, and D. B. Clarke, "Ticket Fare Optimization for China’s High-Speed Railway Based on Passenger Choice Behavior," Discrete Dynamics in Nature and Society, vol. 2017, Feb. 2017, Art. no. e6237642. DOI: https://doi.org/10.1155/2017/6237642
J. Zheng and J. Liu, "The Research on Ticket Fare Optimization for China’s High-Speed Train," Mathematical Problems in Engineering, vol. 2016, Aug. 2016, Art. no. e5073053. DOI: https://doi.org/10.1155/2016/5073053
A. Nikseresht and K. Ziarati, "A Demand Estimation Algorithm for Inventory Management Systems Using Censored Data," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2215–2221, Dec. 2017. DOI: https://doi.org/10.48084/etasr.1517
Z. Xiaoqiang, M. Lang, and Z. Jin, "Dynamic pricing for passenger groups of high-speed rail transportation," Journal of Rail Transport Planning & Management, vol. 6, no. 4, pp. 346–356, Jan. 2017. DOI: https://doi.org/10.1016/j.jrtpm.2017.01.001
M. Qin, Y. Li, and G. Che, "Railway passenger ticket pricing policy portfolio," in International Conference on Logistics, Informatics and Service Sciences, Sydney, NSW, Australia, Jul. 2016, pp. 1–5. DOI: https://doi.org/10.1109/LISS.2016.7854432
G. Dutta and P. Ghosh, "A passenger revenue management system (RMS) for a National Railway in an Emerging Asian Economy," Journal of Revenue and Pricing Management, vol. 11, no. 5, pp. 487–499, Sep. 2012. DOI: https://doi.org/10.1057/rpm.2012.10
K. T. Talluri and G. J. van Ryzin, The Theory and Practice of Revenue Management. Boston, MA, USA: Springer, 2005. DOI: https://doi.org/10.1007/b139000
P.-S. You, "An efficient computational approach for railway booking problems," European Journal of Operational Research, vol. 185, no. 2, pp. 811–824, Mar. 2008. DOI: https://doi.org/10.1016/j.ejor.2006.12.049
X. Jiang, X. Chen, L. Zhang, and R. Zhang, "Dynamic Demand Forecasting and Ticket Assignment for High-Speed Rail Revenue Management in China," Transportation Research Record, vol. 2475, no. 1, pp. 37–45, Jan. 2015. DOI: https://doi.org/10.3141/2475-05
M. Riss, J. Cote, and G. Savard, "A new revenue optimization tool for high-speed railway: finding the right equilibrium between revenue growth and commercial objectives," in 8th World Congress on Railway Research, Seoul, Korea, Dec. 2008.
P. Hetrakul, "Discrete choice models for revenue management," Ph.D. dissertation, University of Maryland, College Park, MD, USA, 2012.
S. S. Azadeh, M. Hosseinalifam, and G. Savard, "The impact of customer behavior models on revenue management systems," Computational Management Science, vol. 12, no. 1, pp. 99–109, Jan. 2015. DOI: https://doi.org/10.1007/s10287-014-0204-z
W. L. Cooper, T. Homem-de-Mello, and A. J. Kleywegt, "Models of the Spiral-Down Effect in Revenue Management," Operations Research, vol. 54, no. 5, pp. 968–987, Oct. 2006. DOI: https://doi.org/10.1287/opre.1060.0304
S.-W. Kim, "The impact of customer buying behavior on the optimal allocation decisions," International Journal of Production Economics, vol. 163, pp. 71–88, May 2015. DOI: https://doi.org/10.1016/j.ijpe.2015.02.009
J. G. Wilson, C. K. Anderson, and S.-W. Kim, "Optimal booking limits in the presence of strategic consumer behavior," International Transactions in Operational Research, vol. 13, no. 2, pp. 99–110, 2006. DOI: https://doi.org/10.1111/j.1475-3995.2006.00537.x
A. Sen and A. X. Zhang, "The newsboy problem with multiple demand classes," IIE Transactions, vol. 31, no. 5, pp. 431–444, May 1999. P. Belobaba and L. R. Weatherford, "Comparing Decision Rules that Incorporate Customer Diversion in Perishable Asset Revenue Management Situations," Decision Sciences, vol. 27, no. 2, pp. 343–363, 1996. DOI: https://doi.org/10.1111/j.1540-5915.1996.tb00856.x
I. S. Yeoman and U. McMahon-Beattie, "The turning points of revenue management: a brief history of future evolution," Journal of Tourism Futures, vol. 3, no. 1, pp. 66–72, Jan. 2017. DOI: https://doi.org/10.1108/JTF-11-2016-0040
B. Vinod, "Evolution of yield management in travel," Journal of Revenue and Pricing Management, vol. 15, no. 3, pp. 203–211, Jul. 2016. DOI: https://doi.org/10.1057/rpm.2016.15
A. K. Strauss, R. Klein, and C. Steinhardt, "A review of choice-based revenue management: Theory and methods," European Journal of Operational Research, vol. 271, no. 2, pp. 375–387, Dec. 2018. DOI: https://doi.org/10.1016/j.ejor.2018.01.011
M.-E. A. Martinez, M.-A. G. Borja, and J.-A. M. Jimenez, "Yield Management As A Pricing Mechanism," Review of Business Information Systems, vol. 15, no. 5, pp. 51–60, Sep. 2011. DOI: https://doi.org/10.19030/rbis.v15i5.6018
R. K. Roy, Design of Experiments Using The Taguchi Approach: 16 Steps to Product and Process Improvement. New York, NY, USA: Wiley, 2001.
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