Optimization Models for Scheduling of Jobs.

Area of Science:

• Operations Research
• Logistics Management
• Aerospace Engineering

Background:

• Logistics centers face complex scheduling challenges in aircraft maintenance and modification.
• Existing job schedules (start times, durations, workstation assignments) are known.
• The need exists to efficiently schedule new jobs into available facility resources.

Purpose of the Study:

• To develop an optimized scheduling strategy for new jobs in aircraft maintenance hangars.
• To improve the efficiency of resource allocation within a single facility (hangar) with multiple workstations (bays).

Main Methods:

• Development of a mixed integer quadratic programming (MIQP) model for the scheduling problem.
• Creation of a heuristic procedure inspired by bin packing techniques to overcome computational complexity.
• Enhancement of the heuristic through the application of local optimality conditions.

Main Results:

• A computationally efficient heuristic procedure was developed for the aircraft maintenance scheduling problem.
• The heuristic offers a practical solution for real-time scheduling decisions in logistics centers.
• The method provides a viable alternative to exact solutions of complex optimization models.

Conclusions:

• The proposed heuristic method effectively addresses the challenge of scheduling new jobs in aircraft maintenance facilities.
• This approach offers a balance between solution quality and computational speed for practical logistics operations.
• The study contributes to optimizing resource management in the aerospace MRO (Maintenance, Repair, and Overhaul) sector.