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

机译:不确定需求下机队效率的平台设计:空中机动司令部(AMC)的应用

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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.
机译:本文介绍的方法结合了多学科设计优化和运筹学的方法,以改善与能源效率相关的国防采购决策。这项工作的重点是为美国空军空中机动司令部采购新飞机,该司令部是国防部最大的燃料消耗国。这里的方法通过明确考虑不确定性,在空中机动司令部的背景下扩展了机队级购置决策的先前工作。该方法同时选择了对新货运飞机的要求,预测了该新飞机的尺寸,重量和性能,并且还将新飞机与现有飞机一起分配以满足货运需求。最终车队的燃油效率为比较提供了一个指标。该方法结合使用的抽象和假设,成功地描述了影响机队水平指标的新型货机。分配问题结合了类似于调度的功能,以解决时间驱动的操作约束。这项研究的结果证明了使用空中机动司令部全球空中运输执行系统数据集的简单三路径网络和22基地网络的方法。

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