OPTIMAL SEQUENCING IN ATM COMBINING GENETIC ALGORITHMS AND GRADIENT BASED METHODS TO A BILEVEL APPROACH

摘要

A bi-level algorithm is developed to determine the optimal arrival sequence w.r.t a specific upper level objective function, e.g. minimiz- ing pollutant emissions or maximizing runway throughput. Within a sequence it is assumed that all aircraft are operated optimally (lower level optimization), minimizing individual fuel consumption. However, all aircraft trajecto- ries adhere to constraints imposed by the up- per level, such as time and distance separation. The algorithm combines a direct optimal con- trol method for solving the lower level problem with a genetic algorithm, which is applied to the upper level combinatorial problem. The lower level problems are fully dis- cretized by applying a trapezoidal collocation scheme provided by FALCON.m [1] and subse- quently solved utilizing the interior point NLP solver IPOPT [2]. The discretization is per- formed during initialization of the algorithm and reused during execution to minimize com- putational effort. For the upper level prob- lem an efficient mutation operator is intro- duced, which exploits the information con- tained within the Lagrange multiplier of the discretized arrival time constraint. The algorithm is validated against a test case scenario comprising five aircraft destined for runway 08L of Munich airport, which en- ter the terminal maneuvering area within four minutes at multiple way points. Aircraft dy- namics are represented by a model derived from BADA 3. The performance of the algo- rithm allows the application on a pre-tactical level for a limited number of arriving aircraft.