| Summary |
This study deals with the baggage unloading carousels (BUCs) assignment problem for
inbound flights in an airport. Actual arrival times of inbound flights are general uncertain due
to some unexpected events (e.g., inclement weather) in practice. The uncertain arrival times may adversely affect the operations of baggage unloading in the airport and could significantly
downgrade the service quality of the airport. This study considers the uncertain arrival times of
inbound flights and represents the uncertainty using a discrete probability distribution. In order
to effectively describe the assignment and the schedule of (BUCs), this study proposes a baggage carousel flow network and constructs the stochastic optimization model based on the proposed network. The objective is to minimize the expected value of unanticipated schedule delay costs, the walking distance for passengers to baggage claim, and the difference between the optimal assignment and the historical assignment of flights to BUCs.
Using the Taoyuan International Airport as a case study, this study obtained the inbound
flight data and the BUC assignment data in August, 2019 from the airport operator, and generated problem instances using the data. The problem instances of the proposed stochastic optimization model were solved using Gurobi Optimizer. The results show the model is able to effectively generate the optimal BUC assignment to inbound flights. This study also conducted a set of sensitivity analyses to examine the impact of the model parameters on the solution.
Moreover, the solutions of the deterministic model and the stochastic model are compared to
evaluate the benefits of using the stochastic model. In addition to the methodological contribution, the proposed approach has practical application value and can provide a reference for the airport operator to perform the BUC assignment for inbound flights. |
