Date of Award

3-2023

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Richard Dill, PhD

Abstract

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate and risk. The DTP method generates optimal COAs that minimize risk while completing objectives at deadlines chosen by the commander. When compared to a naive COA generation method, the DTP COAs incur 367% less risk while completing all objectives in approximately half the time.

AFIT Designator

AFIT-ENG-MS-23-M-057

Comments

Approved for public release: 88ABW-2023-0279

A 12 month embargo was observed.

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