A Heuristics Algorithm for Centralized Deicing Scheduling Problem

Abstract

For the solution of the deicing delay, the greedy randomized adaptive search procedure (GRASP) was applied to optimize the scheduling scheme. Based on the simulation software, the departure data of an international airport was used to verify the validity of the proposed algorithm and compare the simulation results with the first-come, first-served (FCFS), greedy without availability check (GWOAC), and greedy with availability check (GWAC). In the model, the cost of the deicing time window, the deicing queue time and the moving distances of aircraft were included in the objective function. The simulation experiments on 283 instances results show that GRASP outperforms other algorithms on aircraft deicing queue time and take-off delay time. Furthermore, in order to obtain an optimal scheduling scheme, vehicles' workload is balanced by adjusting the model after evaluating the working hours of each deicing vehicle.