Abstract

Campus safety requires strategic and efficient patrolling to ensure security. This study optimizes campus safety patrol routes at The College of Wooster using mathematical and computational approaches while utilizing historical and simulated incident data. Two models were developed: a fixed patrol route, optimized via Traveling Salesperson Problem (TSP) framework to achieve uniform coverage; and an adaptive route, formulated using Mixed-Integer Programming (MIP) to prioritize high-risk areas in real-time. The fixed route ensures structured patrols with high campus-wide coverage in minimal time, while the adaptive model provides better coverage in high-risk areas, improving efficiency. Comparison with the existing system shows that while the optimized models improve efficiency, they lack the comprehensive coverage achieved by the current system that makes use of foot, vehicle, and camera surveillance. The study highlights the trade-offs between efficiency and full coverage, suggesting hybrid approaches that balance systematic coverage with dynamic risk-based patrolling.

Advisor

Murphy, Jake

Department

Mathematics

Disciplines

Applied Mathematics

Keywords

Optimization, Operations Research, Campus Safety, Mixed-Integer Programming

Publication Date

2025

Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis

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