Acquisition War-Gaming Technique for Acquiring Future Complex Systems: Modeling and Simulation Results for Cost Plus Incentive Fee Contract

Abstract

This paper provides a high-level discussion and propositions of frameworks and models for acquisition strategy of complex systems. In particular, it presents an innovative system engineering approach to model the Department of Defense (DoD) acquisition process and offers several optimization modules including simulation models using game theory and war-gaming concepts. Our frameworks employ Advanced Game-based Mathematical Framework (AGMF) and Unified Game-based Acquisition Framework (UGAF), and related advanced simulation and mathematical models that include a set of War-Gaming Engines (WGEs) implemented in MATLAB statistical optimization models. WGEs are defined as a set of algorithms, characterizing the Program and Technical Baseline (PTB), technology enablers, architectural solutions, contract type, contract parameters and associated incentives, and industry bidding position. As a proof of concept, Aerospace, in collaboration with the North Carolina State University (NCSU) and University of Hawaii (UH), successfully applied and extended the proposed frameworks and decision models to determine the optimum contract parameters and incentives for a Cost Plus Incentive Fee (CPIF) contract. As a result, we can suggest a set of acquisition strategies that ensure the optimization of the PTB.

Systems-of-Systems MS&A for Complex Systems, Gaming and Decision for Space Systems

“…3.1.2 MS&A approach using multi-criteria decision support system for system architecture assessment in pre-milestone A To address the system requirements trade space challenges, the proposed system architecture assessment approach should be based on the required warfighter capabilities and market survey results to identify desired TEs for providing the required capabilities. The MS&A approach is derived from [15,16], where system architecture assessment is based on the technical performance, market, cost, and schedule risks. Technical performance risk is referred to as technology risk and is quantified using Technology Readiness Level (TRL), while market risk is related to market uncertainty and is quantified by Manufacturing Readiness Level (MRL).…”

“…Rough Order Magnitude (ROM) Cost, TRL and MRL data are collected from a market survey for cost and schedule risk assessment. Figure 5 illustrates a recent advanced MS&A approach for system architecture assessment and an example of an architecture solution output [15,16]. The approach uses game theory combined with the war-gaming concept to assess and optimize the system architecture solutions using the market survey results.…”

“…DAA-PWGE) and Contractor game engine (a.k.a. KTR-PWGE) for assessing and optimizing the architecture solutions under USG perspective and contractor perspective, respectively [15,16]. The objective of the USG game engine is to minimize cost and technical risk using an appropriate PCF for trading off the affordability and technical requirements.…”

“…The objective of MS&A models and tools is to selects the best architectural solution and associated architecture solution type for risk assessment. Classification of architecture solution type depends on the system and associated systems-ofsystems requirements and associated market and technology risks (i.e., uncertainty) [15,16]. Figure 6 describes an acquisition strategy mapping framework and shows the mapping of requirement type to architecture solution type according to various market and technology risks.…”

“…In practice, during the pre-Milestone A, the USG team can also play the contractor role to determine the win-win acquisition strategy from both USG and contractor perspectives. Detailed description of the game engines can be found in [15,16].…”