Dynamic Adaptive Optimization Methodology Of C2 Organization Structure Under Uncertainty Mission Environment

The highly complexity and dynamic uncertainty of information warfare requires agile Command and Control (C2) organization to acquire and maintain the overall confrontation superiority. The agile C2 organization is characterized by well adaptability. How to timely carry out the adaptive optimization on the current organization structure, according to the effect of dynamic arriving uncertainty events on the C2 organization capabilities under mission environment, comes into being one of the primary problems in the research of C2 organization. The existing methods of organization structure adaptive optimization generally select the whole mission execution period as optimization horizon, and mostly adopt organization reconfiguration method, the effect of which is not ideal.The problem of C2 organization structure adaptive optimization still needs further research.Focusing on the capability measurement of C2 organization under uncertainty mission environment, adaptive optimization model of C2 organization structure and dynamic adaptive optimization method, this paper makes the following contributions:1. C2 organization capabilities measurement is proposed. The definition and description of C2 organization elements and organization structure are improved, and particularly, in order to measure decision capabilities requirement of mission and effect of uncertainty factors on the decision capabilities, the decision capability attributes of task and decision-makers are considered. The decision capabilities and resource capabilities provided by C2 organization to complete mission effectively are defined, the corresponding measurement parameters of which are proposed respectively, and then the definition and description of measurement parameters are given. The category, source of uncertainty factors and theirs influence on organization under uncertainty mission environment, as well as optimizing function of organization structure to organization capabilities are analyzed, optimal relation between organization structure variables and organization capabilities is established.2. Layered dynamic adaptive optimization method of C2 organization structure is proposed. The C2 organization structure adaptive optimization (COSAO) model to maximize organization capability is built based on the analysis of C2 organization capabilities under uncertainty mission environment. In view of complex association between structure variables and capabilities measurement, adaptive optimization strategy based on layered organization structure is proposed, which reduces the complexity of COSAO model solution. In view of dynamic uncertainty of COSAO model, through introducing rolling horizon theory, the dynamic adaptive optimization strategy based on rolling horizon is presented. Using horizon decomposition principle and optimization of multiple shorter horizons that triggered flexibly, this strategy is computationally efficient while adapting to the uncertainty change of environment. Combined with two adaptive optimization stategies, the layered dynamic adaptive optimization method of C2 organization structure (SLDAO) is proposed, which reduces dynamic uncertainty and complex association during COSAO model solution.3. Dynamic adaptive optimization of organization decision-layer structure based on rolling horizon procedure (RHP) is proposed. The mathematical model of measurement parameters for C2 organization decision capabilities is established, which reflects the satisfaction degree of mission decision capability requirements from the perspective of quantity and quality of completed task. The events of decision implementation capability loss and intensity change of task decision-load which influence on the decision capability are discussed. The uncertainty events parameters are defined. Based on the analysis of organization decision capability, the adaptive optimization model of decision layer structure is built, according to the dynamic uncertainty of which, the adaptive optimization method of decision-layer structure based on RHP (DLSDAO-RHP) is presented, RHP strategy elements including the prediction window, rolling window, optimization sub-problems and rolling mechanism are designed. This method can adjust the length of optimization horizon according to uncertainty degree under mission environment, and reduce the solution uncertainty by decomposing the initial problem into multiple optimization sub-problems in shorter horizon. According to optimization sub-problems in optimization horizon, the nested improved simulated annealing algorithm (NISA) is proposed. Case analysis and comparison experiments indicate that DLSDAO-RHP can improve the organizational decision capability under uncertainty mission environment through multiple sub-problems optimization in shorter horizons.4. Dynamic adaptive optimization method of C2 organization resource-layer structure based on key events is proposed. The mathematical model of measurement parameters for C2 organization resource capabilities is established, which reflects the satisfaction degree of mission resource capability requirements from the perspective of quantity and quality of completed task. The events of platforms loss, task addition and cancellation, and task-processing temporal variation are discussed. The uncertainty events parameters are defined. Based on the analysis of organization resource capability, the adaptive optimization model of resource-layer structure is built, according to the dynamic uncertainty of which, two-stage dynamic adaptive optimization method based on key events (TAOBKE) of resource-layer structure is presented. This method can trigger adaptive optimization of resource-layer structure in real-time through the effect of uncertainty events on organization resource capability. Case analysis and comparison experiments indicate that TAOBKE can improve the organization resource capability effectively under uncertainty mission environment.5. The comprehensive case to analyze dynamic adaptive optimization of C2 organization structure is designed. Taking a landing compaign in multi-arms combined operation for example, this paper synthetically discusses the effect of influencing events of decision capability and resource capability on C2 organization, and proves the presented SLDAO method. The case analysis illustrates the necessity of dynamic adaptive optimization and adjustment of organization structure under uncertainty mission environment as well as the well performance of SLDAO method. Through layered C2 organizaton structure, the SLDAO method reduces organization reconfiguration effectively, and ensures the stability of C2 organization structure. Along with the increasing of uncertainty events, SLDAO method can control the increase of structure adjustment cost, therefore which has the obvious advantages faced with the frequent occurrence of uncertainty events.