Problem:

create pair of of people with similar properties. Minimize difference between members of a pair

Solution

Algorithm for optimal node pairing that minimizes the total distance between paired nodes. This is essentially a minimum-weight perfect matching problem.I’ve created a comprehensive implementation of optimal node pairing algorithms. Here’s what the code includes:

Key Components:

1. Node Class: Represents a point in 2D space with distance calculation
2. Multiple Algorithm Approaches:
   • Greedy: Fast O(n³) algorithm that repeatedly finds closest pairs
   • Nearest Neighbor: O(n²) algorithm that pairs each node with its nearest unpaired neighbor
   • Approximation with Local Search: Improves greedy solution using 2-opt style swaps
   • Brute Force Optimal: Guaranteed optimal solution via backtracking (exponential time)

Algorithm Trade-offs:

• Greedy: Fast but may get stuck in local optima
• Nearest Neighbor: Faster, good for large datasets, decent quality
• Approximation: Best balance of speed and quality for medium datasets
• Brute Force: Perfect solution but only practical for small instances (≤8-10 nodes)

Usage Recommendations:

• Small datasets (≤8 nodes): Use brute force for guaranteed optimal
• Medium datasets (10-100 nodes): Use approximation algorithm
• Large datasets (>100 nodes): Use nearest neighbor or greedy

The code includes a test function that demonstrates all algorithms on a sample dataset, showing the total distance and individual pairs for each approach. You can easily adapt it for your specific coordinate system or distance metric.

Mengukur detak jantung menggunakan WiFi. Pakai ESP32 dan Raspberry Pi juga bisa. https://news.ucsc.edu/2025/09/pulse-fi-wifi-heart-rate/ papernya:

• https://news.ucsc.edu/wp-content/uploads/2025/08/Pulse_Fi_short_paper_iotdcoss.pdf
• https://bpb-us-e1.wpmucdn.com/sites.ucsc.edu/dist/d/1595/files/2025/05/Pulse_Fi_short_paper_iotdcoss.pdf