Developed and Optimized Python Algorithms

📅 2023-09-07 — Session: Developed and Optimized Python Algorithms

🕒 23:20–23:40
🏷️ Labels: Python, Algorithms, Optimization, Error Correction, Greedy Algorithm, Dynamic Programming
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to implement and optimize various Python algorithms for specific problems, including minimum discontentment calculation, suspicious balances, and segmentation for choripán stands.

Key Activities

• Implemented the min_descontento function to optimize the order of correcting exams based on discontentment calculations.
• Corrected errors in the Python function for calculating minimum discontentment, focusing on variable usage.
• Developed the saldos_sospechosos function to determine the nature of numbers in relation to a final balance, acknowledging multiple valid solutions.
• Explored iterative and greedy approaches to the suspicious balances problem, comparing them with dynamic programming and backtracking methods.
• Implemented a segmentation strategy for choripán stands, using Python to divide stands into segments and place supply points efficiently.
• Discussed a greedy algorithm approach for the choripán problem, examining its efficiency and limitations.

Achievements

The session successfully implemented and refined multiple algorithms, enhancing efficiency and addressing specific problem constraints.

Pending Tasks

Further exploration of dynamic programming and backtracking methods for the suspicious balances and choripán problems could provide more comprehensive solutions.