📅 2024-10-26 — Session: Enhanced Multi-Day Task Scheduling with OR-Tools
🕒 21:10–22:25
🏷️ Labels: Task Scheduling, Or-Tools, Python, Dataframe, Constraints
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance a multi-day task scheduling system using Python and Google OR-Tools, focusing on improving constraint management, debugging, and dynamic task replication.
Key Activities
- Task Scheduling Framework: Implemented a structured approach for scheduling tasks over three days using OR-Tools and Pandas, including calendar visualization.
- Dynamic Constraints: Developed a model to apply constraints dynamically from a CSV file, improving flexibility and maintainability.
- Error Handling: Addressed TypeErrors and indexing errors in task replication and constraint handling, ensuring robust error management.
- DataFrame Manipulation: Updated DataFrame logic to accurately reflect scheduled tasks across multiple days, preventing data overwrites and ensuring clarity.
- Frequency Constraints: Integrated frequency-based replication to distribute tasks evenly across days, enhancing schedule balance.
Achievements
- Successfully implemented dynamic constraint processing and frequency-based task replication, improving the scheduling model’s adaptability.
- Resolved errors related to data conversion and task variable management, enhancing the system’s reliability.
- Improved the DataFrame structure to better represent multi-day task schedules, ensuring comprehensive task visualization.
Pending Tasks
- Further testing is needed to ensure the robustness of the frequency-based replication under varying task loads and constraints.
- Explore additional optimization techniques to enhance the scheduling efficiency and performance.