RUNTIME ANALYSIS OF BENDERS DECOMPOSITION AND DUAL ILP ALGORITHMS AS APPLIED TO COMMON NETWORK INTERDICTION PROBLEMS

Attacker-defender models help practitioners understand a network’s resistance to attack. An assailant interdicts a network, and the operator responds in such a way as to optimally utilize the degraded network. This thesis analyzes two network interdiction algorithms, Benders decomposition and a dual integer linear program approach, to compare their computational efficiency on the shortest path and maximum flow interdiction problems. We construct networks using two operationally meaningful structures: a grid structure designed to represent an urban transportation network, and a layered network designed to mimic a supply chain. We vary the size of the network and the attacker's budget and we record each algorithm’s runtime. Our results indicate that Benders decomposition performs best when solving the shortest path interdiction problem on a grid network, the dual integer linear program performs better for the maximum flow problem on both the grid and layered network, and the two approaches perform comparably when solving the shortest path interdiction problem on the layered network.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Going the distance for protein function prediction: a new distance metric for protein interaction networks

Due to an error introduced in the production process, the x-axes in the first panels of Figure 1 and Figure 7 are not formatted correctly. The correct Figure 1 can be viewed here: http://dx.doi.org/10.1371/annotation/343bf260-f6ff-48a2-93b2-3cc79af518a9In protein-protein interaction (PPI) networks, functional similarity is often inferred based on the function of directly interacting proteins, or more generally, some notion of interaction network proximity among proteins in a local neighborhood. Prior methods typically measure proximity as the shortest-path distance in the network, but this has only a limited ability to capture fine-grained neighborhood distinctions, because most proteins are close to each other, and there are many ties in proximity. We introduce diffusion state distance (DSD), a new metric based on a graph diffusion property, designed to capture finer-grained distinctions in proximity for transfer of functional annotation in PPI networks. We present a tool that, when input a PPI network, will output the DSD distances between every pair of proteins. We show that replacing the shortest-path metric by DSD improves the performance of classical function prediction methods across the board.MC, HZ, NMD and LJC were supported in part by National Institutes of Health (NIH) R01 grant GM080330. JP was supported in part by NIH grant R01 HD058880. This material is based upon work supported by the National Science Foundation under grant numbers CNS-0905565, CNS-1018266, CNS-1012910, and CNS-1117039, and supported by the Army Research Office under grant W911NF-11-1-0227 (to MEC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

GAME-THEORETIC MODELS FOR RAPID OPERATIONAL AIRLIFT NETWORK DESIGN IN CONTESTED ENVIRONMENTS

The growing threat of conflict with near-peer adversaries requires a robust air-routing plan to transport personnel and cargo effectively. In developing these plans, the U.S. Air Force’s Air Mobility Command (AMC) must account for the dynamic nature of inter-theater operations in a contested environment. Currently, AMC planners predominantly calculate resource allocations manually, which contributes to slower plan implementation and potentially suboptimal solutions. Starting with a proven AMC model, which provides an optimal use of aircraft, cargo allocation, and airfields, we add model features that help determine how to attack this airlift network, optimally delaying the delivery of cargo to operationally relevant locations. The results identify vulnerabilities and provide AMC planners with a prescription of airfield resource allocation that maximizes the movement of cargo. This model delivers a quantitative assessment of an adversary's (whether weather or competitor) ability to delay the mission that can be used to guide policymakers in providing a robust air mobility capability.Outstanding ThesisLieutenant Commander, United States NavyApproved for public release. Distribution is unlimited