Service network design optimization for Army Aviation lift planning

Abstract

The need for optimized aviation lift planning is becoming increasingly important as the United States and her allies participate in the Global War on Terror (GWOT). As part of a comprehensive effort, our nation's fighting forces find themselves conducting operations around the globe, with this trend likely to increase, even as budget constraints limit the number of personnel and amount of equipment that is deployed. While much attention has been given to airline schedule optimization and fleet planning. the challenge of Army Aviation lift planning is unique in that it must be able to adapt to changing requirements and missions on a daily basis. In this thesis, we model Army Aviation lift planning as a service network design problem, and propose two heuristic algorithms, which compare favorably to current human planning systems. Furthermore, we apply these heuristic algorithms to long term asset planning and capacity requirement estimation for future military scenarios, and analyze how passenger flexibility affects the need for capacity.