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Modeling Airlift Operations for Humanitarian Aid and Disaster Relief to Support Acquisition Decision-Making

机译:为人道主义援助和救灾建模空运业务,以支持收购决策

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In a fiscally constrained environment, it is crucial that both equipment manufacturers and defence invest in technology that shows marked operational improvement. A priori identification of cost-benefit at the early acquisition stage is often limited and incomplete, leading to poor value propositions. This conundrum motivates the need to develop a method to evaluate technologies such as levels of autonomy, stealth capability, improved engines, etc. and make tradeoffs against operational measures of performance and effectiveness (MOP/Es) rather than solely against vehicle performance characteristics. The objective of this study is to create an environment in which those trades against MOEs could be performed rapidly to inform technology investment and acquisition decision-making. This environment is built on top of representative models of a discrete event simulation of disaster relief airlift operations to compare technology modifications or vehicle acquisition options rapidly against operational measures of effectiveness.
机译:在一项财政限制的环境中,对于设备制造商和国防投资至关重要,这是表现出明显的运营改善的技术。在早期收购阶段的成本效益的先验识别通常有限和不完整,导致价值差的主张。这一难题激发了开发一种方法来评估自治,隐形能力,改进发动机等技术的方法,并使权衡免于对性能和有效性(MOP / ES)的运作措施,而不是仅针对车辆性能特征。本研究的目的是创造一个环境,其中可以迅速履行对抗MOE的交易,以便为技术投资和收购决策提供信息。这种环境是基于灾害救济空运操作的离散事件模拟的代表性模型之上,以快速地反对有效性运算措施的技术修改或车辆采集选择。

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