Defense Capability Development Optimization Presented by: Dr. Mazal Date: 13 June 2024 Introduction - Scientific and technical State of the Art within management science rapidly evolves. - It brings new opportunities and qualities that were unimaginable before. - Management staff today could implement advanced methods and components in real time. - Armed forces' optimal management and development planning can be difficult due to the high level of uncertainty linked with the future security environment and the evolution of military technology. - Traditionally, strategic decisions were made based on intuition and experience. - Advancements in scientific capabilities now offer highly rational and extended opportunities for strategic decision-making activities that minimize the use of time, material/human resources, and cost. Current Situation In Military Capability Planning - Strategic decisions are based mainly on empirical-intuitive approaches, which very quickly reach hypothetical boundaries. - While advanced military M&S tools are primarily used for education, research, and development, some attempts have been made to use them in strategic decision-making. - Inconsistent level of perception. - The definition of capabilities is very general and provides a vast space for interpretation. - In practice, "optimization" efforts face several well-known problems, such as: • High complexity and uncertainty of the environment affected by the solution; • Strategic (defense) personnel's insufficient awareness of modern technology and advanced methodologies; • High administrative congestion of responsible staff hindering the investigation and development of alternative solutions; • Inclination to establish and follow "old-fashioned" bureaucratic procedures; • The capability planning process is part of a complex procedural legislative framework, which is very difficult to adjust by itself; • Lack of specialized SW solutions adapted to the specific problem; • Possibly others. Advanced Approach To The Military Capability Planning - The solution employs various methods from different fields, including linear algebra, probability theory, statistics, random processes, operational art, algorithm development, modeling and simulation, operational research, linear, nonlinear, and dynamic programming, graph theory, automation, artificial intelligence, and software engineering - The solution architecture can be derived from the intuitive-logical framework of the operational performance graph consolidation and the search for the optimal armed forces configuration (CAF) regarding the maximum resilience to future threats, but considering an "optimal" investment plan that also fits within the anticipated defense budget. Advanced Approach To The Military Capability Planning - Solution Architecture - 1. Elementary structural unit definition - 2. Time step specification - 3. The armed forces' initial (model) structure definition - 4. Conceptual model of the organizational structure development - 5. State model of organizational structure development - 6. Compilation of a cost evaluation graph - 7. The forecast of the organization's development - 8. Compilation of operational scenarios - 9. Constructive wargaming - 10. The calculation of the maximum total operational efficiency - 11.Reverse search for the minimum path - 12. Filtering the final graph - 13. Transforming the CAF into military capabilities The Armed Forces' Initial (Model) Structure Definition - The armed forces' initial (model) structure has to be created from the elementary structural unit (ESU) and its "operational-efficiency calibration," which is based on its current state. - It quantifies the coefficients of operational efficiency of individual components or systems within the organizational structure. - ESU development is a relatively complex problem that is solved by geo-tactical analyses that support ESU's doctrinal behavior in a particular operational situation. - Pictures demonstrate some operational analyses within tactical behavior optimization. Compilation Of A Cost Evaluation Graph - Compilation of a "shadow" cost evaluation graph of all configurations transition at time n to the state n + i, where i denotes a discrete time step - It is possible to calculate the financial demands of the particular armed forces configuration and determine whether a given strategy fits within the planned budget in this respect, the strategy means a path in the state graph of armed forces configurations - It is difficult to accurately quantify financial investments representing the relationship between the transformation of individual ESUs to higher quality levels - In any case, for the initial solution and automation of the vast configuration's assessment, the cost could be empirically estimated or statistically evaluated based on previous experience of modernization of individual capabilities. - The total costs for a given year form the sum of linear combinations of the vector RV, and other individual components of the transformation costs, according to: Constructive Wargaming And Maximization Of Operational Efficiency - Constructive wargaming of all configurations of CAF with the assumed enemy configuration (all options, minimally optimistic and pessimistic) for each operational scenario and selected geographical area in a statistically representative amount (ideally a hundred times or more for each operational scenario). - Automating all parts of the solution chain is necessary to calculate the solution's intended scope and depth. - Calculating the maximum total operational efficiency of each node of the development graph of the CAF (for each configuration). - This method uses, for example, the Critical Path Method (CPM), Dijkstra, or A* algorithm to find the minimum path to each node in the directed mathematical graph. - The procedure for calculating the first part of the solution can be divided into two phases. - The first phase seeks the optimal solution as a minimum path to each organizational structure configuration graph node through the minimal sum of operational efficiency coefficients. - The second phase (described further) is preceded by the solution stability analysis of the resulting graph, where the second phase finds an optimal sequence for the configuration of the CAF within a selected period (usually decades). Conclusion - The issue of computer support for decision-making processes at all levels of command is currently highly actual. - It generally offers a significant increase in efficiency in various human domains, and with the rapid development of modern technologies, its importance continues to grow. - The main goal was to design a basic algorithmic framework (approach) for the armed forces' capability development and optimization. - It creates optional opportunities for its subsequent evolvement within the following projects or activities - The quality of the final results depends on various aspects, potentially presenting another topic for future research. - All the main SW components and theoretical procedures are available for the problém's initial solution. - Despite this fact, the overall concept is a very challenging task, and its implementation is achievable within several years. - The research and development efforts will certainly pay off to invest.