Honors Theses

Advisor

Raúl Ordóñez, Ph.D.

Department

Electrical and Computer Engineering

Publication Date

4-22-2026

Document Type

Honors Thesis

Abstract

Homelessness is a complex social issue influenced by a wide range of economic, social, and health related factors. Traditional methods for measuring homelessness, such as point-in-time counts, provide valuable snapshots of the population but do not capture the dynamic processes that lead individuals into or out of homelessness. This work presents a system dynamics model designed to simulate homelessness trends within Montgomery County, Ohio. The model represents the county population using five primary states: general population, at-risk, homeless, supportive housing, and unaccounted individuals. To better capture heterogeneity within the population, the homeless and supportive housing states are further decomposed into subpopulations representing key socioeconomic risk factors. Population counts and transition rates are derived from county-provided homelessness service data and point-in-time measurements. The model also incorporates public funding as a system input, enabling analysis of how changes in resource allocation influence long-term homelessness outcomes. Using a state-space difference equation modeling framework implemented in MATLAB, the system allows for simulation of alternative policy scenarios and identification of critical points within the homelessness system. The resulting framework provides a predictive tool that can support data-informed decision making for homelessness prevention and resource allocation within Montgomery County.

Permission Statement

This item is protected by copyright law (Title 17, U.S. Code) and may only be used for noncommercial, educational, and scholarly purposes.

Keywords

Undergraduate research


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