A Mathematical Modeling Approach
Open Access DepositedOptimizing Baggage Handling Systems Design for Southwest Airlines
Passenger baggage handling is an important process in any airport, ensuring the timely and safe transportation of passenger’s baggage from the point of check-in to the point of destination. The Mishandled Bag Rate (MBR) is a performance indicator used in the baggage handling process. The MBR is the percentage of bags that are lost, damaged, delayed, or misrouted during the baggage handling process. The praxis is the formulation of a mathematical model to be used in the optimal deployment of Explosive Detection Systems (EDS) and Makeup Units (MU) to minimize the MBR. The praxis uses quantitative research methodology, with CART regression as the primary modeling technique, linear regression, Poisson regression, polynomial regression, and random forest regression as secondary techniques.Pearson correlation analysis is conducted to show the linear relationship between each independent variable and the dependent variable. The results of the Pearson correlation analysis revealed strong negative correlations between the independent and the dependent variables. Results obtained from the regression analysis revealed that both independent variables are significant predictors of MBR, and the number of EDS and MU units had a significant effect on the MBR. With each increase of a unit of EDS and MU, the MBR was found to significantly decrease. An optimal combination of EDS and MU that can be deployed in a baggage handling system at an airport has been identified in practice. As a result of the praxis, several recommendations are proffered to the airport managers. The optimization framework and results of this praxis can be used as a reference point for resource allocation and system optimization in order to improve the performance and efficiency of baggage handling operations and consequently enhance the travel experience for passengers.
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