Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

We study the maintenance task scheduling problem for an aircraft fleet in uncertain environment from viewpoint of robust optimization. Given a daily horizon, tasks delegated to shop should be scheduled such way that sufficient aircrafts are available on time meet demand planned missions. The either activities or unexpected repair jobs when major fault is detected during preor after-flight check each mission. availability skilled labour main constraint. propose formulation so duration subject unstructured uncertainty due environmental and human factors. As result specific structure primary model non-convexity feasible space, classical optimization methods cannot applied. Thus, we e-Conservative tandem with Monte-Carlo sampling extract set all solutions corresponding various disturbance vectors. Since one-way sampling-then-optimization approach does not guarantee probabilistic feasibility, employ hybrid simulation-optimization ensure provided by scenarios. experimental results confirm scalability proposed methodology generating optimal solutions, satisfying conservatism levels scenarios irrespective size.