Enhanced Vehicle Beddown Approximations For the Improved Theater Distribution Model

Gathering insight into the theater distribution process can be a complex task, especially when estimating potential beddown solutions. Coming up with a low cost feasible mixture of cargo vehicles that will support distribution of military personnel and goods within theater is currently a high priority for force flow analysts at USTRANSCOM. In the past, analysts used a trial and error simulation process that was iterative and time consuming. Recent research has produced the Improved Theater Distribution Model (ITDM), which presents a less time consuming, more precise method to estimate beddown allocations. Improving on this research, two linear programming methods were developed and added to the ITDM that reduce baseline beddown approximations. Because daily usage cost and initial beddown cost was included, this ultimately presented a lower cost feasible solution when modeling theater distribution. The improved beddown solutions generated from post-processing results of the ITDM can be used as baselines for further distribution analysis. Within the construct of the model, precise set notation is carried over from the Improved Theater Distribution Model and slightly altered to reduce the generation of unnecessary variables and constraints with large-scale problems

A Mixed Integer Programming Model for Improving Theater Distribution Force Flow Analysis

Obtaining insight into potential vehicle mixtures that will support theater distribution, the final leg of military distribution, can be a challenging and time consuming process for United States Transportation Command (USTRANSCOM) force flow analysts. The current process of testing numerous different vehicle mixtures until separate simulation tools demonstrate feasibility is iterative and overly burdensome. Improving on existing research, a mixed integer programming model was developed to allocate specific vehicle types to delivery items, or requirements, in a manner that would minimize both operational costs and late deliveries. This gives insight into the types and amounts of vehicles necessary for feasible delivery and identifies possible bottlenecks in the physical network. Further solution post-processing yields potential vehicle beddowns which can then be used as approximate baselines for further distribution analysis. A multimodal, heterogeneous set of vehicles is used to model the pickup and delivery of requirements within given time windows. To ensure large scale problems do not become intractable, precise set notation is utilized within the mixed integer program to ensure only necessary variables and constraints are generated

Quicklook Air Mobility Modeling

This research is a framework for understanding issues in modeling the military aspect of space, with particular regard to capturing its value. Space power is a difficult and far-reaching topic, with implications that go beyond the military aspects. The United States military increasingly relies on space-based systems and information for success in daily operations. Telecommunications, navigation and timing, intelligence, surveillance, reconnaissance, and weather prediction are instances of services that have become dependent on satellite systems. If this reliance on space is not fully understood, U.S. national security will be at risk as the result of space information degradation or denial. This research effort attempts to break new ground in organizing the interactions and interdependencies among space doctrine, space systems, system owner/operators, and space-based information users. An illustrative example, using GPS, is then examined to explore the approach. Analysis of GPS as it affects JDAM accuracy is modeled using the GPS Interference And Navigation Tool (GIANT)

Modeling and Analyzing the Effect of Ground Refueling Capacity on Airfield Throughput

This thesis develops five analytical models to understand the current ground refueling process, to optimize the airfield configuration and to determine the refueling policy which maximizes throughput, the primary measure of airfield efficiency. This study models the airfield refueling process as a continuous time Markov process to adequately represent the inherent stochastic nature of the transitory ground refueling system and provide an analytical evaluation of various airfield configurations. Also, the study provides an optimal refueling policy to minimize the number of aircraft on the ground which in turn minimizes the average amount of time aircraft spend on the ground in a fifth model, a Markov decision process solved by a linear program. By accomplishing this, higher throughput rates can be achieved by allowing a higher aircraft arrival rate into the airfield