ORCID Identifier(s)

0000-0002-5780-2667

Graduation Semester and Year

2021

Language

English

Document Type

Thesis

Degree Name

Master of Science in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Caroline Krejci

Abstract

Agent-based modeling is frequently used to produce geospatial models of transportation systems. However, reducing the computational requirements of these models can require a degree of abstraction that can compromise the fidelity of the modeled environment. The purpose of the agent-based model presented in this thesis is to explore the potential of a volunteer-based crowd-shipping system for rescuing surplus meals from restaurants and delivering them to homeless shelters in Arlington, Texas. Each iteration of the model’s development has sought to improve model realism by incorporating empirical data to strengthen underlying assumptions. This thesis describes the most recent iteration, in which a method is presented for selecting eligible volunteers crowd-shippers based on total trip duration, derived from real-time traffic data. Preliminary experimental results illustrate the impact of adding trip duration constraints and increasing the size of the modeled region on model behavior, as well as illuminating the need for further analysis.

Keywords

Crowd-shipping platforms, Agent-based modeling, Network effects

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

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