Algorithm Engineer · 2023

Gator-Taxi

University of Florida — Advanced Data Structures

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The Challenge

Campus taxi dispatching suffered from inefficient ride allocation — pickup times averaged 10+ minutes, riders experienced long waits, and taxis sat idle between shifts. The challenge: optimize O(n) brute-force dispatch into an O(log n) system.

The Approach

Designed a dual-indexing architecture combining Red-Black Trees for geospatial proximity lookups with Min-Heaps for priority-based request scheduling. This allowed O(log n) insertion, deletion, and nearest-neighbor queries.

The Solution

Red-Black Tree index for real-time geospatial location tracking and nearest-taxi lookup
Min-Heap scheduler for priority queue request management
Dual-indexing architecture enabling O(log n) operations across both dimensions
Feature extraction pipeline reducing idle time through predictive positioning

The Impact

0% Faster Pickups

0% Shorter Wait Times

0% Less Idle Time

0% Test Cases Passed

Tech Stack

C++ Red-Black Trees Min-Heaps Algorithm Design

“Sometimes the most impactful optimization is choosing the right data structure — Red-Black Trees and Min-Heaps turned a brute-force dispatch into a logarithmic-time system.”

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