Before Covid19, airports worldwide are faced with limited capacity issues, and predicting the passenger demand at the airport is vital for resource planning at various customer touchpoints ranging from check-in counters and immigration. In this case study, we use one-year historical data to forecast the departure demand for each airline and develop a simulation model to determine the number of check-in counters required to optimize the resource utilization at the airport. This paper's overall objective is to uncover the real-world business problem in the classroom setting, and the authors will share how to go through this case study in detail.
Airport check-in counters assignment using predicted passenger load: A Case Study
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