Optimized Bus Stop Placement

Divide & Conquer · Closest Pair · Clustering Trees

This mini web tool demonstrates how to collect spatial data, detect closest pairs, build clustering trees, and finally place bus stops optimally for a campus or city region.

Start with Module 1 Jump to Evaluation

Pipeline

  1. Module 1 Data Collection & Spatial Preprocessing
  2. Module 2 Closest Pair & Clustering Tree Formation
  3. Module 3 Optimal Bus Stop Placement & Evaluation

Why Divide & Conquer?

The closest pair of points problem can be solved in O(n log n) using divide and conquer, which scales better than checking all pairs for large datasets.

Clustering Trees

By repeatedly merging the most similar clusters, we form a hierarchical clustering tree. The centroids of clusters represent potential bus stop locations.