Next Generation Scheduling Systems (NGSS) Customer Need There is a persistent shortage of well-qualified aviators within the U.S. Military. Specifically, the training process to become an aviator is complex and marked by several key events. Current flight scheduling is designed around business case rules with a "linear flow" of students per scheduled event. This scheduling process is manual and is complicated by each student's continually evolving training requirements and the natural fluctuations in asset availability. A more efficient approach is one in which an artificial intelligence-enabled platform optimizes the student's curriculum, instructor allocations, and resource scheduling. For example, when planning for upcoming training requirements, past student performance is utilized as a predictor of current student performance and subsequently predicts anticipated student progression and anticipated asset requirements for an entire training regimen. Additionally, when scheduling flight training events, an enhanced derived solution would consider multiple competing variables such as weather, maintenance, and instructor availability. Such a platform would be able to optimize scheduling based on multiple competing priorities and provide a more efficient and reliable scheduling approach. High-Level Capabilities The following high-level capabilities are required in the system. 

• Seamlessly interface with existing training management systems and databases 

• Allow students and instructors to monitor progress

• Allow manual manipulation of student progress through various flight courses, if desired by an instructor. 

• Suggest courses of action for students to optimize training and reduce the overall training length - without a reduction in quality. Kindly develop functional performance requirements for the above