**5.3 Models and tools supporting space systems acquisition strategy development and optimization using game theoretic**

Like Section 5.2, the MS&A models and tools presented here were also implemented in Matlab [18, 19, 21–24]. The Matlab simulation models also implemented static Bayesian with complete and incomplete information games and associated pure and mixed games for the acquisition strategy development and optimization. The current Matlab models implemented three common contract types, including FFP, FPIF and CPIF. **Figure 14** illustrates the Matlab GUI of the tool for developing optimum acquisition strategy with associated contract parameters under both USG and contractor perspectives [16, 24]. The figure shows a notional case with Pure game, four potential contractors bidding, with and without enterprise databases. Note that enterprise database includes program of records with past programs data from public open sources. Non-enterprise database includes only notional survey data collected from potential bidding contractors.

**Figure 14** also shows a notional use case for four contractors (a.k.a. Suppliers) bidding the contract assuming that (i) there are three contractors (Suppliers #1, #2 and #3) bidding using optimum Nash strategy and one contractor (Suppler #4) bidding using non-optimum strategy, (ii) the selected USG reference architecture is obtained from MS&A models and tool presented in Section 5.2, and (iii) CPIF is the selected contract type based on the risk assessment results for the selected system architecture solution. Bidding results show that Supplier #1 has

#### **Figure 14.**

*Matlab GUI for system acquisition strategy development and optimization.*

the winning bidding strategy with 37% wins, followed by Supplier #3 with 37% wins and Supplier # 2 with 25% wins. Supplier #4 has the lowest winning bid with 5% due to non-optimum bidding strategy, i.e. not using Nash strategy. Acquisition results captured the key features of the winning bidding strategy, including USG saving for overrun and underrun cases, underrun and overrun formulas.

Again, the MS&A models and tool presented in this section are not intended to predict what contractor has the winning bidding strategy. The intention is to gain insight into the winning bidding strategy based on the selected optimum architecture solution for the development and selection of the USG reference architecture for RFP preparation.

#### **6. Conclusion and way-forward**

The systems-of-systems MS&A approaches presented in this chapter focused on recent advanced framework, processes and available models and tools for supporting pre- and post-Milestone A of the US defense acquisition life cycle with capability-based acquisition approach. Proposed MS&A approaches were derived from the USG point of view using systems-of-systems perspective to address optimum reference system architecture solu¬tion and associated acquisition strategy for acquiring the selected solution meeting desired cost, schedule and technical performance. The proposed MS&A approaches and associated Matlab models and tools were primarily focused on pre-Milestone A and developed based on SOSE CONOPS modeling and simulation of resilient space SOSE operations, Bayesian games combined with war-gaming concept and multi-criteria decision support system for optimizing system architecture solutions and associated acquisition strategy. Available Matlab tools were presented for assessing space SOSE CONOPS, evaluating alternative system architecture solutions and optimizing acquisition strategy of common contract types, such as FFP, FPIF and CPIF [15–24]. In general, the systems-of-systems MS&A approaches presented here can be extended to support other non-defense system and acquisition life cycle from non-government perspectives. Existing Matlab models and tools presented in Section 5 can also be extended to non-space SOSE CONOPS, Bayesian dynamic games with other contract types (such as FPEPA, FPAF, CPAF and CPFF).

*Systems-of-Systems MS&A for Complex Systems, Gaming and Decision for Space Systems DOI: http://dx.doi.org/10.5772/intechopen.100007*

The author hopes that this chapter provides MS&A concepts and source of ideas for the readers to develop commercial systems-of-systems frameworks, processes, models and tools for supporting of their own MS&A works.
