Platform Design for Fleet-Level Efficiency under Uncertain Demand: Application for Air Mobility Command (AMC)

Abstract

The approach presented here combines approaches from multidisciplinary design optimization and operations research to improve energy efficiency-related defense acquisition decisions. The work focuses upon the acquisition of new aircraft for the US Air Force Air Mobility Command, which is the largest consumer of fuel in the Department of Defense. The approach here extends prior work in fleet-level acquisition decisions, in the context of Air Mobility Command, by explicitly considering uncertainty. The approach simultaneously selects requirements for a new cargo aircraft, predicts size, weight and performance of that new aircraft, and also allocates the new aircraft along with existing aircraft to meet cargo transportation demand. Fuel efficiency of the resulting fleet provides a metric for comparison. The approach, with the abstractions and assumptions used, successfully provides a description of a new cargo aircraft that impacts fleet-level metrics. The allocation problem incorporates scheduling-like features to account for time driven operational constraints. Results in this study demonstrate the approach for a simple three-route network and 22-base network, using the Air Mobility Command Global Air Transportation Execution System dataset.