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The optimal college application problem (MS thesis and slides)

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CollegeApplication

Working repo for my MS thesis, “The College Application Problem,” at Seoul National University. You can download the PDF (thesis/paper-en.pdf or thesis/paper-ko.pdf) in your preferred language, or clone the repo and run make to build from the LaTeX source.

If you found this research useful, please consider citing either our arXiv paper or this thesis:

I’d prefer that you use this GitHub repo as the URL (so that I can fix typos 🤣), but if your style guide requires an “official” link, you can use http://www.dcollection.net/handler/snu/000000172202, which comes from the SNU thesis archive. The Korean text there matches the v0.1.0 release tagged here.

Table of contents

Directory Contents Formats English Korean Coauthors
paper_alma/ A concise paper on the cardinality-constrained college admissions problem (Alma’s problem), focusing on the greedy algorithm and student welfare analysis. PDF, LaTeX Yim Seho, Sung-Pil Hong
paper_ellis/ A concise paper on the knapsack-constrained college admissions problem (Ellis’s problem), focusing on its computational complexity and exact and approximate algorithms. PDF, LaTeX
poster/ A one-sheet summary of the research prepared for JuliaCon 2022, with an emphasis on the OptimalApplication.jl package. PDF, ODT
slides_03min/ Slides and script for the JuliaCon 2022 presentation. Click here to view them in your browser. HTML
slides_08min/ Slides and script for a presentation at the department’s research fair. PDF, LaTeX
slides_15min/ Slides and script for a presentation at the spring 2022 conference of the Korean industrial engineering society (대한산업공학회). PDF, LaTeX
slides_25min/ Slides and script for my defense presentation. PDF, LaTeX
thesis/ My MS thesis. The contents are essentially the same as the arXiv paper, but updates appear here first. PDF, LaTeX

For the associated Julia package, which implements the algorithms provided in paper, see https://github.com/maxkapur/OptimalApplication.

Comments and suggestions are welcome via email (maxkapur@gmail.com) or GitHub pull request.