Publications

To help effectively plan the management and modernization of its large and diverse fleet of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) commissioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This report contains a description of the organizational fleet structure and a thorough explanation of the business rules that the CPAT formulation follows involving performance, scheduling, production, and budgets.

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In order to effectively plan the management and modernization of its large and diverse fleet of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) commissioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thorough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation.

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Materiel availability (Am) is a new US Department of Defense Key Performance Parameter (KPP) implemented through a mandatory Sustainment Metric consisting of an Availability KPP and two supporting Key System Attributes (KSAs), materiel reliability and ownership cost. Sandia National Laboratories (Sandia), in conjunction with several US Army organizations, developed the analytical foundation, assumptions, and brigade-level modeling approach to support lifecycle, fleet-wide Am modeling and analysis of a complex Army weapon system. Like operational availability (Ao), Am is dependent on reliability, but Am is also affected by other factors that do not impact Ao. The largest influences on A m are technology insertion and reset downtimes. Am is a different metric from Ao. Whereas Ao is an operational measure, Am is more of a programmatic measure that spans a much larger timeframe, additional sources of downtime, and add itional sources of unscheduled maintenance. © 2011 IEEE.

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