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A methodology for comprehensive strategic planning and program prioritization

01/2008;
Source: OAI

ABSTRACT This process developed in this work, Strategy Optimization for the Allocation of Resources (SOAR), is a strategic planning methodology based off Integrated Product and Process Development and systems engineering techniques. Utilizing a top down approach, the process starts with the creation of the organization vision and its measures of effectiveness. These measures are prioritized based on their application to external world scenarios which will frame the future. The programs which will be used to accomplish this vision are identified by decomposing the problem. Information is gathered on the programs as to the application, cost, schedule, risk, and other pertinent information. The relationships between the levels of the hierarchy are mapped utilizing subject matter experts. These connections are then utilized to determine the overall benefit of the programs to the vision of the organization. Through a Multi-Objective Genetic Algorithm a tradespace of potential program portfolios can be created amongst which the decision maker can allocate resources. The information and portfolios are presented to the decision maker through the use of a Decision Support System which collects and visualizes all the data in a single location. This methodology was tested utilizing a science and technology planning exercise conducted by the Unites States Navy. A thorough decomposition was defined and technology programs identified which had the potential to provide benefit to the vision. The prioritization of the top level capabilities was performed through the use of a rank ordering scheme and a previous naval application was used to demonstrate a cumulative voting scheme. Voting was performed utilizing the Nominal Group Technique to capture the relationships between the levels of the hierarchy. Interrelationships between the technologies were identified and a MOGA was utilized to optimize portfolios with respect to these constraints and information was placed in a DSS. This formulation allowed the decision makers to assess which portfolio could provide the greatest benefit to the Navy while still fitting within the funding profile. Ph.D. Committee Chair: Mavris, Dimitri; Committee Member: Bishop, Carlee; Committee Member: Costello, Mark; Committee Member: Kirby, Michelle; Committee Member: Schrage, Daniel

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    ABSTRACT: There are many times in which a critical choice between proposed system architectures must be made. Two situations in particular motivate this dissertation: a "Cambrian explosion" when no dominant rchitecture has arisen, and times in which developments enable challenges to a dominant incumbent. In each situation, the advance of core technologies is key. This dissertation features a new computing technique to systematically explore the interaction of technological progress with architectural choices. This technique is founded upon a graph theoretic formulation of architecture, which enables the consideration of multifunctional components and modularity v. synergy trades. The technique utilizes a genetic algorithm formulated for graphs, and a solver that automatically constrains and optimizes component design variables. The use of quantitative technology models, graph theoretic formulation, and optimization algorithms together enables a systematic exploration of both time and combinatorial spaces. The quantitative results of this exploration enhance the strategic view of technology planners. Ph.D. Committee Chair: Mavris, Dimitri; Committee Member: Costello, Mark; Committee Member: German, Brian
    01/2009;

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