Hi Giorgio,
I understand that you want to analyze each configuration of activities in an assembly line balancing problem with different execution times for tasks executed by humans, robots, or in cooperation. Here are some steps for you to approach this problem:
- Define the execution times for each task and configuration. Create a matrix where each row represents a task and each column represents a configuration, with the corresponding execution time.
- Generate all possible configurations using the Cartesian product. You can use a function like `allcomb` to generate all combinations of configurations for the tasks.
- Initialize variables to store the best configuration and its time. Set the initial best time to infinity.
- Iterate over each configuration. For each configuration:
Get the execution times for the tasks in the current configuration.
Calculate the total time for the current configuration by summing the execution times.
Update the best configuration and best time if the current configuration is faster.
- Display the best configuration and its total time.
By following these steps, you can analyze each configuration of activities and find the configuration that results in the minimum total time for the assembly line balancing problem.
