Institute for Software Research International
School of Computer Science, Carnegie Mellon University


Organizational Morphing Technology

Kathleen M. Carley, Natalia Y. Kamneva, Jeff Reminga

December 2004

Institute for Software Research International (ISRI)
Center for Computational Analaysis of Social and Organizational Systems (CASOS)

Keywords: Morphing Technology (MT), meta-matrix, Hamming distance, minimal total path cost, A* search algorithm, admissible heuristic, cost function, edge betweenness centrality, Simulated Annealing, Simplified Memory-Bounded A* Algorithm, Dynamic A* Algorithm (D* search algorithm)

Each unit (organization, team or group) has a particular structure. This structure is often referred to as the command and control structure. This structure is efficiently represented as a series of interconnected graphs of networks where the nodes in the network are personnel, resources, tasks, and knowledge. Such representation of units as networks makes it possible to compare and contrast the command and control structure of different units. It also makes it possible to find an optimal organizational design given a particular mission.

There is a need in social network analysis to predict and manage changes with organizations and teams. Altering the command and control structure of organizational units might be expensive and have drastic impact on their performance. Hence there is a need for automated tools that can locate cost effective and minimally disruptive paths of change. These tools should be able to formalize a theory of organizational adaptation and provide the basis for its understanding and predicting. We called the methodology that we are using to develop such tools a constraint based morphing technology.

This report considers different methods of searching the optimal path between the source and goal structure. We introduce in this report the new optimization method of finding a cheapest path, based on the Simulated Annealing algorithm. We also introduce a new approach for computing a cost function, based on the Dynamic Network Analysis (DNA) metric called the Edge Betweenness Centrality.

20 pages

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