📅 2023-09-07 — Session: Developed and Optimized Python Algorithms for Multiple Problems
🕒 23:20–23:40
🏷️ Labels: Python, Algorithms, Optimization, Error Correction, Greedy Algorithm
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to develop and optimize several Python algorithms, addressing specific computational problems and exploring different algorithmic approaches.
Key Activities
- Implemented the
min_descontentofunction in Python to calculate total discontentment by optimizing the order of correction based on times and coefficients. - Corrected an error in the
min_descontentofunction related to variable usage, ensuring accurate computation of discontentment. - Developed the
saldos_sospechososfunction in Python to determine the nature of numbers in relation to a final balance, indicating if they should be positive, negative, or ambivalent. - Explored iterative and greedy approaches to the ‘Suspicious Balances’ problem, comparing their efficiency and limitations with dynamic programming and backtracking methods.
- Designed a segmentation strategy for choripán vendor distribution, implementing a Python solution to divide stalls into segments and place vendors at midpoints.
- Analyzed a greedy algorithm approach for the choripán problem, discussing its efficiency and comparing it with other algorithmic strategies.
Achievements
- Successfully implemented and corrected multiple Python functions to solve specific algorithmic problems.
- Explored and documented various algorithmic strategies, enhancing understanding of their efficiency and limitations.
Pending Tasks
- Further exploration of dynamic programming and backtracking methods for the ‘Suspicious Balances’ and choripán problems to identify optimal solutions.