Improved discrete Harris Hawks optimization with heuristic approximation and rolling horizon control strategy for aircraft landing problem

With the increasing air traffic flow and more complicate configuration of air routes in the airport terminal area, studies on the traditional aircraft landing problem (ALP) that only considers runway or landing scheduling are no longer sufficient to meet practical needs. Further consideration such as route selection, en-route separation, conflict avoidance in merging waypoints is needed in consistent to the real air traffic management. Hence, this paper extends the study from the landing scheduling to the whole approaching and landing scheduling within the terminal area. More realistic constraints including route selection from all paths, attitude relevance speed range, en-route and wake separation, maximum position shift, arrival time windows, conflict avoidance in merging waypoints are considered in the optimization model. Then, the solving method is studied. After a comparative study of mainstream algorithms, the improved discrete Harris Hawks optimization (IDHHO) is presented. Many strategies for HHO such as new individual generation, preferred exchange, preferred insertion, random perturbation are added. The prey escape energy update equation is improved. To cope with large-scale situation, heuristic approximation (HA) and the multiple waypoint rolling horizon control strategy (MWRHC) are proposed to accelerate the solving speed of IDHHO. Based on the data of Guangzhou Baiyun International Airport, computations under low, medium and high traffic density are conducted. The experimental tests verify the validity of the model and algorithm. The computational results show MWRHC-IDHHO-HA can greatly reduce the solving time on the expense of small optimality loss. The presented model and algorithm have been used in the practical ALP management system called Arrival Management (AMAN).