大本营生活质量标准化和提高

Patrick K. Kuiper, S. Kolitz, V. Tarokh
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摘要

美国陆军有超过66,000名士兵在世界各地参与应急行动。目前的预算限制和不确定的全球安全环境要求尽可能有效地执行这些行动。基地营地是士兵被部署到应急行动时居住的安全区域。在应急行动期间,基地营造成了重大的财政和战术负担,士兵生活质量欠佳的决定大大增加了成本。生活质量(Quality of life, QOL)是指直接维持士兵执行任务效能的与安全、任务无关的服务。目前的美国陆军大本营战术、技术和程序(TTPs)没有充分说明QOL服务,应该制定更详细的理论来支持作战单位执行应急行动。在这项调查中,我们采用定量方法来选择决策,提高生活质量和通知学说。我们利用美国陆军纳蒂克士兵研究、发展和工程中心(纳蒂克实验室)开发的生活质量函数和资源消耗数据,建立了一个模型,在燃料、水、废水和固体废物四种基本资源的约束下提高生活质量。我们采用混合整数线性规划建模方法,并执行敏感性分析来评估我们的结果的强度。我们的最终模型是一个机会约束优化,以解决应急操作中与资源可用性相关的不确定性。我们的结果提供的QOL决策减少了资源消耗,同时与当前的ttp相比保持了等效的QOL水平。该模型提供了定量的严谨性,为理论发展提供了具体大本营设计原则的信息。
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Base camp quality of life standardization and improvement
The United States (US) Army has over 66,000 soldiers engaged in contingency operations across the world. Current budgetary constraints and an uncertain global security environment require these operations to be executed as efficiently as possible. Base camps are the secured areas where soldiers live when deployed to contingency operations. Base camps impose a significant financial and tactical burden during contingency operations and sub-optimal soldier quality of life decisions have significantly contributed to costs. Quality of life (QOL) refers to the non-security and non-mission related services that directly sustain the mission effectiveness of soldiers. Current US Army base camp tactics, techniques, and procedures (TTPs) do not sufficiently specify QOL services, and more detailed doctrine should be developed to support combat units executing contingency operations. In this investigation we employ quantitative methods to select decisions that improve QOL and inform doctrine. We leverage a QOL function and resource consumption data developed by US Army Natick Soldier Research, Development and Engineering Center's (Natick Labs) to build a model that improves QOL under the constraints of four fundamental resources: fuel, water, waste water, and solid waste. We employ a mixed integer linear program modeling approach and execute sensitivity analysis to evaluate the strength of our results. Our final model is formulated as a chance constraint optimization to address the uncertainty associated with resource availability in contingency operations. Our results provide QOL decisions that reduce resource consumption while maintaining an equivalent QOL level when compared to current TTPs. The model provides quantitative rigor, informing decision makers of specific base camp design principles for the development of doctrine.
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