Abstract

We present two heuristics based on constraint technology that solve the problem of generating air traffic management contingency plans, which are used in the case of a catastrophic infrastructure failure within EUROCONTROL, the European Organisation for the Safety of Air Navigation. Of the heuristics presented, one is based on constraint-based local search and tabu search, and the other one is a constraint programming and large neighbourhood search hybrid algorithm. The heuristics show that it is feasible to automate the development of contingency plans, which is currently done by human experts; this is desirable for several reasons, for example it would allow the contingency plans to be generated with an increased frequency. The generated plans were evaluated, by EUROCONTROL, to be at least as good as the human-made ones. Document type: Part of book or chapter of book

Abstract

ce congestion is today the most critical issue European Air Traffic Management (ATM) has to face. Current real-time Air Traffic Control (ATC) is achieved by human controllers. One of their main tasks is to keep separation between aircraft, asking to the pilots to do basic avoidance manoeuvres. We propose here two mixed CSP models of this separation issue, combining discrete and continuous variables. An implementation of these models allows to produce optimal solutions for problems where numerous aircraft are conflicting.