## Introduction Task Management Systems (TMS) are a type of software tool used to manage and control multiple tasks within a business. It is a highly organized system that helps to track and visualize tasks related to a project or a process. A TMS allows users to organize tasks, assign responsibilities, and complete tasks efficiently. It can help organizations to maximize productivity and efficiency, improve communication, and ensure that deadlines are met. Additionally, it can help to ensure that tasks are properly tracked and reported. This paper will discuss the process of designing a system to manage and control multiple tasks within an organization.

### Overview Designing a system to manage and control multiple tasks involves creating a task scheduler. This task scheduler will be responsible for managing and controlling the tasks that need to be executed. It will also ensure that tasks are executed in an efficient manner. ### Algorithm 1. Initialize a list of tasks to be executed. 2. Sort the tasks based on priority. 3. Assign a unique ID to each task. 4. Assign a start time and an end time to each task. 5. Create a data structure to store the tasks. 6. Monitor the task list to ensure that tasks are executed in a timely fashion. 7. Execute the tasks in the order specified. 8. Update the data structure with the task execution results. 9. Repeat steps 2-8 until all tasks have been executed. ### Sample Code ``` # Initialize a list of tasks to be executed tasks = [] # Sort tasks based on priority tasks.sort(key=lambda x: x.priority) # Assign a unique ID to each task for task in tasks: task.id = generate_task_id() # Assign a start time and an end time to each task for task in tasks: task.start_time = get_current_time() task.end_time = calculate_task_end_time(task) # Create a data structure to store the tasks task_data = [] # Monitor the task list to ensure tasks are executed in a timely fashion while len(tasks) > 0: task = tasks.pop(0) execute_task(task) task_data.append(task) # Update the data structure with the task execution results for task in task_data: task.status = get_task_status(task) ```