Stochastic seat allocation models for passenger rail transportation under customer choice

Xinchang Wang, Hua Wang and Xiaoning Zhang

Transportation Research Part E: Logistics and Transportation Review, 2016, vol. 96, issue C, 95-112

Abstract: We study the seat allocation problem for passenger rail revenue management, in which a rail operator attempts to determine the optimal quantity of seats to be allocated to each cabin class for each train service. We formulate the problem with single-stage and multi-stage decisions as two stochastic programming models that incorporate passengers’ choice behavior. We transform the stochastic models into equivalent deterministic mathematical programs that are easy to solve. Then, we form a variety of seat allocation polices from the optimal solutions to the seat allocation models. A number of simulation tests are offered to test the policies.

Keywords: Passenger rail; Revenue management; Passenger choice behavior; Seat allocation; Monte-Carlo simulation; Stochastic programming (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (14)

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DOI: 10.1016/j.tre.2016.10.003

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