Holistic fleet optimization incorporating system design considerations

Stephen M. Henry, Matthew J. Hoffman, Lucas A. Waddell, Frank M. Muldoon
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Abstract

The methodology described in this article enables a type of holistic fleet optimization that simultaneously considers the composition and activity of a fleet through time as well as the design of individual systems within the fleet. Often, real‐world system design optimization and fleet‐level acquisition optimization are treated separately due to the prohibitive scale and complexity of each problem. This means that fleet‐level schedules are typically limited to the inclusion of predefined system configurations and are blind to a rich spectrum of system design alternatives. Similarly, system design optimization often considers a system in isolation from the fleet and is blind to numerous, complex portfolio‐level considerations. In reality, these two problems are highly interconnected. To properly address this system‐fleet design interdependence, we present a general method for efficiently incorporating multi‐objective system design trade‐off information into a mixed‐integer linear programming (MILP) fleet‐level optimization. This work is motivated by the authors' experience with large‐scale DOD acquisition portfolios. However, the methodology is general to any application where the fleet‐level problem is a MILP and there exists at least one system having a design trade space in which two or more design objectives are parameters in the fleet‐level MILP.
综合考虑系统设计的整体车队优化
本文中描述的方法实现了一种整体车队优化,同时考虑了车队的组成和活动随时间的变化以及车队内各个系统的设计。通常,现实世界的系统设计优化和车队级采办优化是分开处理的,因为每个问题的规模和复杂性都令人望而却步。这意味着船队级别的计划通常仅限于包含预定义的系统配置,而忽略了系统设计备选方案的丰富范围。同样,系统设计优化通常将系统与机群隔离开来,忽略了众多复杂的组合级考虑因素。实际上,这两个问题是高度相互关联的。为了适当地解决这种系统-车队设计的相互依赖,我们提出了一种将多目标系统设计权衡信息有效地纳入混合整数线性规划(MILP)车队级优化的通用方法。这项工作的动机是作者在大规模国防部采办组合方面的经验。然而,如果船队级问题是一个MILP,并且存在至少一个具有设计交易空间的系统,其中两个或多个设计目标是船队级MILP中的参数,则该方法适用于任何应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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