Sponsor:

AFOSR

Research Team:

Manuel D. Rossetti, Edward A. Pohl, Scott J. Mason, Heather L. Nachtmann

Universities Involved:

University of Arkansas

Start Date:

01/01/05

End Date:

12/31/06

Summary:

Through network and modeling analysis, this project attempts on creating a framework that can be used to construct mathematical and logical models of sense and respond (S&R) military logistics networks. S&R act accordingly to three different scenarios corresponding to Dept of Homeland Security threat levels correponding to Department of Homeland Securty threat levels.
Better models and techniques are required in order to be able to evaluate and optimize the new dynamic demand and support networks required by the S&RL concept. In addition to the evaluation and optimization of these new adaptive networks, we must be able to better understand the decision support requirements for humans that are embedded in this complex and rapidly changing environment. Force transformation is creating a modular, highly mobile military that can make decisions across a distributed battlefield and that can apply adaptive (and sometimes autonomous) decision making techniques as force multipliers. These transformations are creating new requirements for logistics capabilities including the ability to dynamically allocate and prioritize sources of supply and the ability to react to commander’s intent given missions, tasks, and desired effects. The concept of S&RL has envisioned the need to rapidly design responsive demand and support networks that can anticipate, predict, and coordinate actions at the strategic, operational, and tactical levels.
In order to better understand the challenges created by this new doctrine, we propose to develop a simulation-based framework for:
* Evaluating adaptable demand and supply networks
* Evaluating new metrics for optimizing and controlling these networks
* Evaluating the new decisions required in such networks, and
* Evaluating the human cognitive capabilities within these networks
The goal of that effort is to provide modeling primitives that will encapsulate the behavior of automatic data collection devices within logistics systems to enable analysts to evaluate their usefulness to decision making within a military logistical context. These types of devices will become increasingly important as our military is transformed by the concept of S&RL.
*New modeling paradigms for supply chain simulation
*New simulation methodologies, mathematical models and techniques for the optimization, performance evaluation, and improvement of future military logistics support networks
*New methods of modeling and incorporating human performance issues and collaborative decision making within an S&RL environment