New model for aircraft landing scheduling using real time algorithms scheduling

Abstract

Expert systems are designed to solve non-regular complex problems using extracted cognitive data and inspiring from the human expertise and its best practices. They are based on the machine performance and its ability to carry out a very large number of complex iterations. The Aircraft Landing Scheduling (ALS) problem has been complex and challenging problem in air traffic control for a long time, In practice, it can formulated as a constrained optimization problem that needs to be solved in real-time. The choice of a task scheduling algorithm in a variable and unpredictable real-time system requires the use of an intelligent expert system, having an evolving knowledge base and a creative inference engine. In this paper we present a general architecture and conceptual concepts of our expert system. This expert system allows the choice of the most optimal scheduling algorithm for aircraft landing scheduling.