Promoting Affordability in Defense Acquisitions: A Multi-Period Portfolio Approach

A Symposium PresentationSymposium PresentationNaval Postgraduate School Acquisition Research Progra

Acquisition Management for System of Systems: Affordability Through Effective Portfolio Management

Disclaimer: The views represented in this report are those of the authors and do not reflect the official policy position of the Navy, the Department of Defense, or the federal government.Excerpt from the Proceedings of the Tenth Annual Acquisition Research Symposium System of Systems ManagementThe research presented in this report was supported by the Acquisition Research Program of the Graduate School of Business & Public Policy at the Naval Postgraduate School. To request defense acquisition research, to become a research sponsor, or to print additional copies of reports, please contact any of the staff listed on the Acquisition Research Program website (www.acquisitionresearch.net).Prepared for the Naval Postgraduate School, Monterey, CA 93943.Approved for public release; distribution is unlimited

Eleventh Annual Acquisition Research Symposium, Thursday Sessions Volume II.

Published April 30, 2014The research presented in this report was supported by the Acquisition Research Program of the Graduate School of Business & Public Policy at the Naval Postgraduate School.The implementation of Better Buying Power policies seeks to achieve affordability across the spectrum of major defense acquisition programs. However, the technical and programmatic challenges associated with sequential decision-making in the acquisition of large scale, increasingly interdependent defense systems prompts a need for quantitative frameworks that can better address the complexities of negotiating capability, schedule, and cost, while fulfilling target objectives of affordability. Our proposed research extends prior funded work and adopts innovations from financial engineering to enable quantitatively informed multistage decision-making under uncertainty. The method provides a means of assessing tradeoffs between capability, cost, and schedule risks, and the ability to objectively make sequentially dependent acquisition decisions on a “portfolio” of systems, towards some desired overarching capability. We adopt a dynamic programming approach using statistical measures and optimization techniques that balance short term decisions against long term implications on dimensions of cost, risk, and schedule. The method is demonstrated for the concept case of multi-stage acquisitions in a naval acquisition scenario.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Formulation and demonstration of a robust mean variance optimization approach for concurrent airline network and aircraft design

Conceptual design of aircraft and the airline network (routes) on which aircraft fly on are inextricably linked to passenger driven demand. Many factors influence passenger demand for various Origin-Destination (O-D) city pairs including demographics, geographic location, seasonality, socio-economic factors and naturally, the operations of directly competing airlines. The expansion of airline operations involves the identificaion of appropriate aircraft to meet projected future demand. The decisions made in incorporating and subsequently allocating these new aircraft to serve air travel demand affects the inherent risk and profit potential as predicted through the airline revenue management systems. Competition between airlines then translates to latent passenger observations of the routes served between OD pairs and ticket pricing—this in effect reflexively drives future states of demand. This thesis addresses the integrated nature of aircraft design, airline operations and passenger demand, in order to maximize future expected profits as new aircraft are brought into service. The goal of this research is to develop an approach that utilizes aircraft design, airline network design and passenger demand as a unified framework to provide better integrated design solutions in order to maximize expexted profits of an airline. This is investigated through two approaches. The first is a static model that poses the concurrent engineering paradigm above as an investment portfolio problem. Modern financial portfolio optimization techniques are used to leverage risk of serving future projected demand using a \u27yet to be introduced\u27 aircraft against potentially generated future profits. Robust optimization methodologies are incorporated to mitigate model sensitivity and address estimation risks associated with such optimization techniques. The second extends the portfolio approach to include dynamic effects of an airline\u27s operations. A dynamic programming approach is employed to simulate the reflexive nature of airline supply-demand interactions by modeling the aggregate changes in demand that would result from tactical allocations of aircraft to maximize profit. The best yet-to-be-introduced aircraft maximizes profit by minimizing the long term fleetwide direct operating costs

Multi-Objective Optimization Of Fleet-Level Metrics To Determine New System Design Requirements: An Application To Military Air Cargo Fuel Efficiency

Naval Postgraduate School Acquisition Research Progra

An Optimization-Based Approach to Determine System Requirements under Multiple Domain-Specific Uncertainties

Naval Postgraduate School Acquisition Research Progra

A Framework to Determine New System Requirements Under Design Parameter and Demand Uncertainties

Naval Postgraduate School Acquisition Research Progra

Capability and Development Risk Management in System-of-Systems Architectures: A Portfolio Approach to Decision-Making

Proceedings Paper (for Acquisition Research Program)In a capability-centered acquisition paradigm, with many interacting and interdependent systems, new approaches are needed for addressing the architecting and acquisition of individual systems to achieve capability targets. Prior research work has explored the use of a Computational Exploratory Model (CEM; Mane & DeLaurentis, 2011) and a Markov network model (Mane, DeLaurentis, & Frazho, 2011) to evaluate complex development networks of system-of-systems (SoS) architectures. The present paper complements this line of work with a portfolio management approach as a decision tool in the acquisition and integration of systems within an SoS context. The approach leverages potential SoS-level capability gains from the integration of individual systems against cost and developmental risks due to system interdependencies. An example application using the Littoral Combat Ship is provided to demonstrate the approach. Congruence of the method in relation to potential benefits of system vendor-level competition in light of open architecture (OA) considerations is also addressed.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Acquisition Management for Systems-of-Systems: Affordability through Effective Portfolio Management

Naval Postgraduate School Acquisition Research Progra

Determining New System Design Requirements to Optimize Fleet Level Metrics Under Uncertainty

Traditional approaches to design and optimize a new system often do not consider how the operator will use this new system alongside the other existing systems. This ﾓhandoffﾔ between the designs of the new system and how this new system operates with the group of systems leads to the sub-optimal performance of the new system when measured with respect to system-level objective. Aircraft design choices made to meet a set of requirements dictate the performance of the aircraft, and the aircraft performance influences how the operator might use the aircraft. Further, the presence of uncertainties in predictions of the new aircraft performance and costs and uncertainties in the amount of payload to transport further exacerbate the problem of determining these requirements. Recent efforts have posed approaches to address this problem, but generally with a deterministic perspective. This research adopts a previously developed subspace decomposition approach and integrates features from robust/reliability based optimization to address the uncertainties and solves two application problemsﾗa military and a commercial airline application. The result demonstrates the ability of the framework to identify the design requirements for the new aircraft, and a posterior analysis indicates that the framework acceptably handles the uncertainties.Naval Postgraduate School Acquisition Research Progra