Date of Graduation

5-2024

Document Type

Thesis

Degree Name

Bachelor of Science in Industrial Engineering

Degree Level

Undergraduate

Department

Industrial Engineering

Advisor/Mentor

Rainwater, Chase

Committee Member/Reader

Sullivan, Kelly

Abstract

Solving combinatorial optimization problems at scale and of sufficiently interesting context has historically required commercial solvers and access to proprietary company data. The development of performant open-source mathematical programming software and crowdsourced datasets has created an opportunity for individuals and enterprises alike to consider alternative solutions to problems with social and personal implications. This honors thesis represents a summary of my undergraduate research work, an application of optimization to three distinct problems connected to these developments. First, we present an optimization study of a last mile delivery system that shows optimization for energy consumption can generate vehicleindependent fuel savings at acceptable tradeoff costs in time and distance. Vehicle assignmentbased savings in a heterogenous fleet environment are identified as well under different explicit capacity prioritization schemes. Open-source technologies have also provided the opportunity to apply optimization techniques to personal decision making to provide clearly improved outcomes without a significant financial investment. To that end, we explore an integer programming formulation for personal task scheduling and a shortest path-based heuristic to create safe and enjoyable running routes of a particular distance. These models are implemented in a publicly available web-app that integrates with the relevant input-output data formats and solution visualization.

Keywords

GVRPTW, OR-Tools, Fuel emissions optimization, Metaheuristic, Sustainability and Vehicle Routing Problem, Last Mile Delivery

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