Timed Cellular Automata for Flight Delay Scheduling Optimization

Abstract

Departure flight scheduling optimization plays an important role in handling flight delays to improve airport resources utility and passenger satisfaction. In this paper, we propose a model with a combination of cellular automaton (CA) and timed automaton (TA) to solve flight delay scheduling problems in two major steps. CA can simulate the aircraft departure queueing process in airport runways through the interaction of cells following some rules while TA is used to control the flight status whether they are delayed or ready to depart using a set of clock values. Although there are few advanced algorithms like linear programming and evolutionary algorithms have been proposed to solve this scheduling problem, these approaches might not be appropriate to apply in the realtime scheduling problems due to long computation times required to find the optimal solution. Since the flight delay scheduling problem is a NP-hardness (non-deterministic polynomial-time hardness), the computational complexity will be more difficult as well as the time amount to find the solution will be greater with an increasing number of aircrafts. Hence, the work to build a simple model using CA and TA to obtain an optimal scheduling solution with time efficiency is presented in this paper. This proposed model is simple yet efficient enough to provide an optimal solution within a short time for real-time airport runway scheduling problems.