Date of Award

3-23-2018

Document Type

Thesis

Degree Name

Master of Science in Operations Research

Department

Department of Operational Sciences

First Advisor

Richard F. Deckro, PhD.

Abstract

Identifying relevant actors using information gleaned from multiple networks is a key goal within the context of human aspects of military operations. The application of a voting theory methodology for determining nodes of critical importance—in ranked order of importance—for a node-aligned multiplex network is demonstrated. Both statistical and qualitative analyses on the differences of ranking outcomes under this methodology is provided. As a corollary, a multilayer network reduction algorithm is investigated within the context of the proposed ranking methodology. The application of the methodology detailed in this thesis will allow meaningful rankings of relevant actors to be produced on a multiplex network.

AFIT Designator

AFIT-ENS-MS-18-M-170

DTIC Accession Number

AD1056433

Share

COinS