Date of Award

3-2025

Document Type

Thesis

Degree Name

Master of Science in Operations Research

Department

Department of Operational Sciences

First Advisor

Ryan B. Walton, PhD

Abstract

With the growing use of simulation across industries, the digital twin remains an underexplored research area, particularly in emergency management and response. Its real-time updating capability is often overlooked due to the misconception that "digital twin" is merely a complex term for simulation. This paper highlights its distinctiveness through an evasion exercise involving two independent entities in a collocated environment. Using a highly integrated virtual environment (HIVE) and internet of things (IoT) devices, we link the physical system with an analytical simulation, demonstrating the impact of lag times in high-pressure scenarios. The computational model leverages agent-based modeling (ABM) and discrete-event simulation (DES) to import real-time data, simulate scenarios, and instantly recommend alternatives for the operator to evade the threat. We generalize this model to other contexts, such as active shooter scenarios and natural disasters, where immediate data-driven decision-making is crucial.

AFIT Designator

AFIT-ENS-MS-25-M-183

Comments

An embargo was observed for this posting.

Approved for public release, Distribution Unlimited. PA Case Number 88ABW-2025-0370

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