Real-time disruption recovery method for apron vehicles based on stability

Abstract

This study investigates the problem of real-time recovery under disruptions such as apron vehicle failures and service delays. The first contribution is the introduction of the concept of spare vehicles, which enhances vehicle utilization and reduces depreciation costs. In addition, planning stability metrics based on service start-time deviation and vehicle routing deviation are designed to quantitatively evaluate the stability of recovery plans. The second contribution is the development of a Disruption Recovery–Dynamic Multi-Period Operational Vehicle Routing Problem with Time Windows (DR-DMPOVRPTW) model. This model considers the delay cost of flight service requests, the total service cost of apron vehicles, and the overall deviation cost. Building on this, a stability-oriented real-time disruption recovery method is proposed. The method introduces a decision mechanism to determine the necessity of recovery actions and designs three real-time recovery strategies from both local and global perspectives, thereby enabling the recovery of operational vehicle scheduling under various disruption scenarios. Large-scale case studies demonstrate the effectiveness of the proposed approach. Compared with local adjustment strategies, global adjustments achieve a superior balance between solution quality and stability, reducing request response time by over 16 %, decreasing the total travel distance of apron vehicles by approximately 14 %, and lowering service start-time deviations by about 62 %. Furthermore, the stability metrics significantly mitigate disruptions to the original schedule, while the use of spare vehicles reduces their average travel distance by more than 40 %. Overall, the findings provide practical insights and empirical references for setting disruption recovery thresholds and determining the appropriate scale of spare vehicles in airport operations.