AI Summary & Key Takeaways
AI InsightIt was assumed that only for airport suitability, Type 5 was not suitable for ADA and KCM airports, and Type 4 was not suitable for KCM airport. it can be reported that a TOOL has been created using the Microsoft Excel program, which enables the evaluation of passenger and cargo demands based on maximizing profit and minimizing losses.
📌 3 Key Takeaways
Abstract
Airlines operate in a highly competitive environment and strive to maximize their revenue by optimizing resource utilization to gain a competitive advantage. In this context, optimizing aircraft allocation for flights is of critical importance for revenue maximization. In airline operations, fleet and aircraft assignments are based on demand forecasts at the beginning of the tariff, so when passenger and/or cargo demand differs from the forecast for a particular flight, the assigned aircraft resource needs to be re-evaluated accordingly. The aim of this study is to create a tool that provides operations managers with a preliminary assessment of demand optimization so that aircraft can be allocated in response to demand changes, taking into account aircraft performance, features, costs and revenues. The data for the variables in the study were obtained through a literature review. The averages of these data were calculated and used for study. It was assumed that only for airport suitability, Type 5 was not suitable for ADA and KCM airports, and Type 4 was not suitable for KCM airport. it can be reported that a TOOL has been created using the Microsoft Excel program, which enables the evaluation of passenger and cargo demands based on maximizing profit and minimizing losses.