A variable neighborhood search algorithm for airport ferry vehicle scheduling problem

Abstract

This paper formulates the airport ferry vehicle scheduling problem as unrelated parallel machine scheduling (UPMS) problem to achieve a better reduction in the weighted sum of flight tardiness. In the UPMS model, the departure time and the estimated end time of each ferry vehicle for each ferry task is simultaneously planned with the allocation of ferry vehicles, and the specific journey of each ferry vehicle for each task is arranged. A variable neighborhood search (VNS) algorithm is proposed to address the model. Three scheduling rules including random allocation, service time in turn (STT), and minimum maximum completion time (MCT) are designed to combine with VNS as comparisons, together with five neighborhood structures suited for the airport ferry vehicle scheduling problem. Comparative experiments are carried out by using two weeks of real flight data from a major international airport in China. Experimental results show the superiority of the proposed MCT initialization combined with VNS (MCT_VNS) for the airport ferry vehicle scheduling problem. The solutions obtained by MCT_VNS can provide the allocation of the airport ferry vehicles to flights that need ferry services.