📅 2023-08-19 — Session: Developed and Analyzed Greedy Pairing Algorithm
🕒 18:55–19:35
🏷️ Labels: Greedy Algorithm, Python, Backtracking, Optimization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal: The session aimed to implement and analyze a greedy algorithm for pairing dancers based on their skills and weights, and to compare its optimality with a backtracking approach.
Key Activities:
- Implemented a greedy algorithm in Python to pair dancers, focusing on skills and weights.
- Analyzed the algorithm’s optimality and compared it with backtracking solutions.
- Discussed the benefits and limitations of greedy versus backtracking strategies in algorithm design.
- Streamlined the code for clarity and efficiency, ensuring optimal local pairings.
Achievements:
- Successfully implemented a functional greedy pairing algorithm.
- Conducted a comparative analysis of greedy and backtracking approaches, with initial results showing optimal pairings using the greedy method.
Pending Tasks:
- Further verification of the greedy algorithm’s optimality through detailed comparison with backtracking results.