Using CPN Modeling and Simulating the Task-Oriented C2 Organization

Task-oriented command and control organization (TC2O) aims to deal with the uncertain war environment. It is a very important problem to evaluating the performance of TC2Os to choose and apply the best one which is most congruent with the mission environment. It is presented that a methodology for setting up the Colored Petri Net (CPN) model of TC2O and simulating the organizational performance. The CPN model of TC2O uses object oriented design approach and it is composed of 3 objects: mission environment, TC2O structure, and resources. In CPN model, the concept of control variable is defined and the model represents all kinds of TC2O parameters by the initial tokens of control variable. At the same time, the switch rules are extracted which can turn the relation of tasks into tokens. Furthermore, the CPN model of TC2O structure is based on Computational and Mathematical Organization Theory (CMOT) and the organization contingency theory. TC2O structure is composed of DMs. Each DM has the same model structure and carries out the tasks with other DMs by communication that includes 5 kinds of messages (i.e. resource requirement message, resource response message, resource movement message, task finish message, information transfer message). Resources are controlled by DMs and used to execute tasks. The CPN model of TC2O is adaptive to the military environment of high time pressure, because the related parameters of TC2O are presented by the initial marking of control variable, and then the CPN model structure of TC2O hasn't to be changed under different mission environments or organization structures. After simulating the CPN model, the performance of TC2Os can be obtained by analyzing the simulation results.

[1]  Krishna R. Pattipati,et al.  Normative design of organizations. II. Organizational structure , 2002, IEEE Trans. Syst. Man Cybern. Part A.

[2]  Krishna R. Pattipati,et al.  Normative design of project-based organizations-Part III: modeling congruent, robust, and adaptive organizations , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[3]  Krishna R. Pattipati,et al.  Design of adaptive organizations , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[4]  Krishna R. Pattipati,et al.  Normative design of organizations. I. Mission planning , 2002, IEEE Trans. Syst. Man Cybern. Part A.

[5]  Kathleen M. Carley,et al.  Organizational designs suited to high performance under stress , 1995, IEEE Trans. Syst. Man Cybern..

[6]  Yuri N. Levchuk,et al.  Normative Design of Organizations — Part I : Mission Planning , 2001 .

[7]  Bao-Xin Xiu,et al.  A novel organizational design methodology based on the theory of information granulation , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[8]  Holly A. H. Handley,et al.  The use of simulation models in model driven experimentation , 1999 .

[9]  Yuri N. Levchuk,et al.  Normative Design of Organizations — Part II : Organizational Structure , 2001 .

[10]  Kathleen M. Carley.  Computational and mathematical organization theory: Perspective and directions , 1995, Comput. Math. Organ. Theory.

[11]  Lars Michael Kristensen,et al.  Model-based development of a course of action scheduling tool , 2007, International Journal on Software Tools for Technology Transfer.

[12]  Krishna R. Pattipati,et al.  An Agent-Based Simulation Model for Organizational Analysis , 2006 .

[13]  Raymond E. Levitt,et al.  The virtual design team , 1998, CACM.