Date of Award

3-2022

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Operational Sciences

First Advisor

Chancellor Johnstone, PhD

Abstract

In the modern operational landscape, strategic decisions are made and executed, under uncertain conditions, with many potential constraints and limited information. The end goal of these decisions is to minimize and mitigate the effect of adversarial threats, which may or may not act in line with previous assumptions. Wargaming is a powerful tool that allows for the practical implementation of theoretical knowledge into real-world scenarios, enhancing decision-makers critical thinking and problem solving skills. Furthermore, including cyber-effects in a wargame leads to a broader decision scope for an entire operation. This research aims to enhance the analytical capabilities and overall usability of the Wargame Commodity Course of Action Automated Analysis Method (WCCAAM) by incorporating cyber-effects in determining optimal blue-team actions. The original WCCAAM model receives mission objectives, available units, and enemy targets as inputs. Then, a multi-commodity flow algorithm (MCFA) is applied to identify the optimal engagement approach to combat a known enemy course of action (COA). This proposed extension of WCCAAM, aptly named the Cyber-Wargame Commodity Course of Action Automated Analysis Method (C-WCCAAM), balances engagement risk with blue-team cyber-effects to combat enemy targets. The resulting model utilizes an MCFA approach within a multi-objective mixed-integer program (MO-MIP) to determine an optimal blue-force COA.

AFIT Designator

AFIT-ENS-MS-22-M-138

DTIC Accession Number

AD1172343

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