Design Methodology Of C2 Organizational Structure And Its Analysis Of Robustness And Adaptivity

How to construct command and control systems under information war with high-level efficiency, in order to put the military organizations matching to mission environment, comes into being one of the difficulties in the fields of command automatization at present. From the existing experimental result, static view cannot give a full description of command and control (C2) organization. Computational organization theory suggests that the most successful organizations tend to be highly flexible. And at the same time, the previously developed systems engineering approaches to organizational design have much shortage however. For the organizations under uncertain environment, the organizational structure must be robust and adaptive.Focusing on the adaptive model of C2 organizations, C2 organizational structure design and its analysis of robustness and adaptivity, this paper makes the following contributions:1. An adaptive C2 organizational model is proposed.In order to describe organization under uncertainty mission environment, we propose an adaptive C2 organizational model, which defines and constrains the required elements of a stable and adaptable organization. Our proposed organizational model contains a structural model, a state model and a transition function, and the definitions and descriptions for them are given respectively. Then, we give the formulation of the organizational transition function. Finally, we discuss the reorganization triggers in detail.2. An organizational structure design methodology based on granular computing is proposed.The theory of granular computing, discussed recently by Prof. Zadeh seems to be a very important issue for computing science and others. We propose the organizational structure design methodology based on granular computing (OSDBGC), by granulating the universe of the problem. Our design process involves three phases, which solve three distinct optimization sub-problems. Phase I (Organizational coordination network - Granulation of platforms and tasks): This phase realize the decision-maker - Platform allocation and decision-maker - Task allocation. The approaches to granulating platforms and tasks are investigated, and the approach to granulating platforms is presented based on genetic algorithm. Phase II (Task scheduling in granular): This phase of our design process decompose the task scheduling problem, with large number of platforms and tasks, into several independent sub-scheduling problems with smaller number of platforms and tasks. Then the tasks-platforms allocations are determined respectively. The method of decomposing the scheduling problem is proposed in this phase. Phase III (Organizational hierarchy tree - decision hierarchy): This phase completes the design by specifying a communication structure and a decision hierarchy to optimize the responsibility distribution and inter-decision-maker control coordination. The description of the problem and the model in mathematics are investigated, which the processing time of task is considered in the definition of decision-maker's workload.The solution is presented by minimizing the overall workload of all decision-makers imposed by the organizational hierarchy tree. The numerical examples show that our design methodology can optimize the multi-objectives in different granular level of universe.3. The robustness of C2 organizational structure is analyzed, and a robust design method of C2 organizational structure is proposed.The design of uncertain mission parameters is discussed, and the concept of mission neighborhood is defined to design the uncertain mission environment. The following uncertainties, introducing variability in the mission and/or resources, are considered in the organizational structure design problem: task measurement errors; task precedence errors; task decomposition. Then the robustness of C2 organizational structure is analyzed, a robust measure is proposed to reflect the redundancies in the task-resource allocation. By extending the organizational structure design methodology based on granular computing, a robust organizational structure design method is proposed, which includes two phases: granulating platforms and designing decision hierarchy. The numerical examples show the need for robust design and the better performance of the proposed design method. Evidently, a robust organizational structure can maintain high levels of performance and degrees of congruence on missions within the range of possibilities. This insensitivity results in a slightly degraded performance on each specific mission, but minimizes the organization's fragility.4. The adaptive cost of C2 organizational structure is analyzed, and an adaptive design method of C2 organizational structure is proposed.The design of dynamic mission parameters is discussed, the following possible changes are considered in the organizational structure design problem: task measurement errors; task precedence errors; task decomposition; changes of platform parameters and decision-maker parameters; entities be detached from the organization or join the organization. The cost of organizational adaptation is analyzed, which constituted by reconfiguration cost and performance cost. We define the cost of reconfiguration between two organizations as the difference between their structures. And performance cost can be viewed as congruence mismatch between organization and mission. Calculating methods of the three kinds of cost are presented respectively. By extending the organizational structure design methodology based on granular computing, an adaptive organizational structure design method is proposed. A numerical example shows the better performance of our design method.