美国陆军航空兵向特遣部队分配通用直升机的两阶段随机编程模型

Russell J Nelson, Jack Werner, Michael G Kay, Russell E King, B. M. McConnell, Kristin Thoney-Barletta
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引用次数: 0

摘要

美国陆军航空部队经常组织成特遣部队,以满足任务要求。他们分配资产的方式会影响其提供航空支援的长期能力。我们提出了一个模型,用于在地理位置分散的特遣部队之间分配通用直升机,以最大限度地减少总飞行时间和按优先级别划分的无支持空中移动空中任务请求(AMR)。我们用一个两阶段随机程序来模拟分配问题,第一阶段问题是将机队的直升机小组分配到特遣部队。然后揭示每个特遣部队的随机需求。第二阶段的美国陆军航空空运行动规划问题被模拟为随机混合整数线性规划(MILP)。在实际应用中,使用空中行动规划启发式大规模解决第二阶段问题,并生成最佳随机解决方案任务部队分配。本文为军事决策者在美军航空资产分配中实际使用所提出的两阶段随机编程模型提供了证据。此外,本研究首次提出了多节点加油的随机编程拨号乘车问题,并为军事航空资产分配决策提供了一个合理的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two-stage stochastic programming model of US Army aviation allocation of utility helicopters to task forces
US Army aviation units often organize into task forces to meet mission requirements. The manner in which they allocate assets affects their long-term capabilities to provide aviation support. We propose a model to allocate utility helicopters across geographically separated task forces to minimize the total time of flight and unsupported air movement air mission requests (AMRs) by priority level. We model the allocation problem with a two-stage stochastic program, with the first-stage problem allocating a fleet’s helicopter teams to task forces. The stochastic demand for each task force is then revealed. The second-stage US Army aviation air movement operations planning problem is modeled as a stochastic mixed integer linear program (MILP). A practical application uses the air movement operations planning heuristic to solve the second-stage problem at scale and generate an optimal stochastic solution task force allocation. This paper provides evidence for the practical use of the proposed two-stage stochastic programming model for US Army aviation asset allocation by military decision-makers. Furthermore, this research provides a novel first formulation of a stochastic programming dial-a-ride problem with multinode refuel and a sound framework for military aviation asset allocation decision-making.
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