Optimization model for large-scale long-term aircraft maintenance scheduling and station assignment

Abstract

The primary focus of the existing aircraft maintenance optimization literature is on short-term aircraft maintenance routing. By contrast, only a few studies address long-term maintenance planning, which predominantly emphasize scheduling decisions: none of them have examined the critical aspect of assigning aircraft to maintenance stations, a key challenge for major airlines with a network of maintenance facilities. Additional research gaps include (1) insufficient consideration of practical maintenance-related constraints (e.g., station access limit and aircraft rotation requirement) and (2) the absence of scalable algorithms capable of solving real-world problem instances involving hundreds of aircraft and dozens of maintenance stations. To fill those gaps, this study introduces a joint optimization model for aircraft maintenance scheduling and station assignment to assist a U.S.-based airline in creating long-term plans for a fleet of over 800 aircraft of multiple subfleet types. To address the computational challenges, we propose two decomposition approaches: one based on decision types and the other on time horizons. Extensive computational experiments using real-world data from the collaborating airline demonstrate that these approaches can reduce computation time by up to 80% with a minimal increase in the optimization objective (less than 2%). The proposed model is expected to streamline maintenance planning efforts and enhance outcomes for aircraft maintenance professionals.