Computational Experimentation to Simplify and Optimize a Large-Scale Simulation of Resourcing Marine Corps Readiness

NPS NRP Executive SummaryComputational Experimentation to Simplify and Optimize a Large-Scale Simulation of Resourcing Marine Corps ReadinessHQMC Programs & Resources (P&R)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Computational Experimentation to Simplify and Optimize a Large-Scale Simulation of Resourcing Marine Corps Readiness

NPS NRP Project PosterMarine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.HQMC Programs & Resources (P&R)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations(CNO)Approved for public release; distribution is unlimited

Computational Experimentation to Simplify and Optimize a Large-Scale Simulation of Resourcing Marine Corps Readiness

NPS NRP Project PosterComputational Experimentation to Simplify and Optimize a Large-Scale Simulation of Resourcing Marine Corps ReadinessHQMC Programs & Resources (P&R)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Computational Experimentation to Simplify and Optimize a Large-Scale Simulation of Resourcing Marine Corps Readiness

NPS NRP Executive SummaryMarine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.Marine Corps Senior Leaders need to allocate service resources to deliver ready units to Combatant Commanders when required. The interactions between resources and readiness are complex, involving thousands of decisions and intermediate outcomes. DC P&R is building a suite of models of operating force elements that propagates the effects of resourcing and policies in the Future Years Defense Plan (FYDP) to quantify the readiness of force elements in each year of the FYDP. When complete, the Predictive Readiness Model (PRM) model will provide DC P&R the means to experiment, visualize, understand, and explain how Marine Corps readiness will change in response to alternative programmatic and/or force management courses of action. The PRM is complex and contains a large number of input variables, many of which are uncertain, propagated through causal chains of interdependent activities. This project will use state-of-the-art high-dimensional design of experiments, high performance computing, and data mining to efficiently explore the developing model. The research team will use these technologies to design and analyze PRM experiments with the objective of simplifying the model by identifying which factors, data sources, and submodels most effect readiness, as well as those with lessor impact. The ability to easily conduct massive experimentation with PRM will also enable analysts to extract more information from the modelincluding identifying the driving factors and data elements, quantifying trade-offs, and ascertaining change-points. The research will also look at advancing design and analysis methods to better explore the PRM. Final products, as appropriate, shall include copies of all software, data, design documents, user manuals, test cases, and any theses, journal articles, or conference proceedings resulting from the research.HQMC Programs & Resources (P&R)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations(CNO)Approved for public release; distribution is unlimited

Smart experimental designs provide military decision-makers with new insights from agent-based simulations

Naval Postgraduate School RESEARCH, 13, 2, Naval Postgraduate School, Monterey, CA, 2003, pp. 20-21, 57-59, 63

Improving Navy recruiting with data farming

Proceedings of the 2016 Winter Simulation Conference T. M. K. Roeder, P. I. Frazier, R. Szechtman, E. Zhou, T. Huschka, and S. E. Chick, eds.Secretary of the Navy Ray Mabus states that people provide “the Navy and Marine Corps’ greatest edge” (Mabus, 2015). To help recruit and manage this dynamic workforce of more than 300,000 active duty Sailors, the Navy uses mathematical models and simulation to assess the potential impacts and risks of changes to force structure, budgets, policies, and the economy. One important model is the Planned Re-source Optimization (PRO) model. PRO is currently being used to inform recruiting resourcing decisions. The decisions may involve, for example, advertising, enlistment bonuses, number of production recruiters, etc. A limitation of PRO is the lack of an interface to facilitate extensive experimentation. This paper summarizes an effort underway to enhance the analytic utility of the PRO model by embedding it in a data farming environment. This enhanced tool is called the “Planned Resource Optimization Model with Ex-perimental Design” (PROM-WED)

Improving Navy MPTE Studies with Model-Driven Big Data

The goal of this research was to improve upon the ability of OPNAV N1 analysts to quickly and efficiently obtain experiment-based information from their computational models. The enhanced information will enable N1’s analysts to better support Navy leadership in resource and policy decisions that shape the future Navy and help it retain and develop its most talented Sailors. This project built on previous collaborations with N1 using data farming to enhance the information gleaned from their Navy talent management models, such as the Officer Strategic Analysis Model (OSAM) model, the Production Resource Optimization (PRO) model, and the Navy Total Force Strength Model (NTFSM). During this research period, (1) Ensign William Desousa (2015) investigated the behavior of economic inputs in NTFSM; (2) Lieutenant Peter Bazalaki (2016) used the new data farming capabilities we developed in OSAM to investigate Surface Warfare Officer (SWO) inventory across a breadth of possibilities; and (3) Lieutenant Allison Hogarth (2016) built, tested, and demonstrated a user interface in Excel that enables users of the PRO model to automatically execute a sophisticated design of experiments—the tool that enables this new capability is known as Production Resource Optimization Model With Experimental Design (PROMWED). In addition to working with the student-officers, the faculty supporting this project performed an empirical study of statistical software packages that may provide better understanding of the high-dimensional behavior of manpower models in the future (Erickson, Ankenman, & Sanchez 2016).Naval Research ProgramPrepared for Topic Sponsor: OPNAV N1; Research POC Name: Mr. Ian AndersoNPS-N16-N154-

Advancing the Application of Design of Experiments to Synthetic Theater Operations Research Model Data

NPS NRP Executive SummaryNavy leadership is interested in initiatives that can potentially increase the responsiveness of campaign analysis. Simulation-based campaign analysis is used to measure risk for investment options in how best to equip, organize, supply, maintain, train, and employ our naval forces. The Synthetic Theater Operations Research Model (STORM) is a stochastic simulation model used to support campaign analysis by the U.S. Navy, Marine Corps, and Air Force. Building, testing, running, and analyzing campaign scenarios in STORM is a complex, time-consuming process. A simulated campaign may span months, involve scores of ships and battalions, hundreds of aircraft and installations, all executing thousands of interconnected missions involving numerous events in time and space. Creating, testing, and approving the inputs for a single design point (DP) requires a significant investment in analysts’ time and computing resources. Consequently, there are limits on the number of DPs that can be produced, executed, and analyzed during a study’s timeframe.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098).Approved for public release. Distribution is unlimited