Highlights We study a stochastic seat allocation problem for passenger rail revenue management with discrete random demands. We develop two stochastic programming models to formulate the problem. We construct a variety of seat allocation policies. We test the policies using simulation studies.
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.
Stochastic seat allocation models for passenger rail transportation under customer choice
2016-10-10
18 pages
Article (Journal)
Electronic Resource
English
Stochastic seat allocation models for passenger rail transportation under customer choice
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