Flamingo Search Algorithm for aircraft landing scheduling

Abstract

Aircraft landing scheduling (ALS) is the process of organizing the arrival and departure of aircraft at an airport. This process is managed by air traffic controllers who use various tools and techniques to ensure that aircraft land and take off safely and efficiently. The goal of aircraft landing scheduling is to minimize delays and maximize the number of aircraft that can be accommodated at the airport. This is done by carefully coordinating the arrival and departure times of aircraft and the number of aircraft that can be safely accommodated. Flamingo Search is an optimization algorithm stimulated by the flamingos’ behavior. A population-based metaheuristic algorithm uses a flock of flamingos to search for the optimal solution to a given problem. The algorithm works by having each flamingo in the flock search for a local optimum solution. The flamingos then communicate with each other and share their solutions. Experiments have demonstrated that our solution is significantly faster and more appropriate for real-time ALS problems compared to conventional optimization techniques, the results showed the superiority of the proposed algorithm over the rest of the algorithms by more than 90%. The suggested method can quickly identify appropriate solutions for all 8 data sets.

Keywords

• Aircraft Landing Scheduling, Flamingo Search Algorithm, Genetic Algorithm, metaheuristic, Optimization