Logistics eCommerce model: Analyzing results

Let's consider an eCommerce business that needs optimization. The main groups of processes involved are:

"Request management",
"Packaging", and
"Shipment and delivery to client".

Each of these groups of processes involves many sub-processes and tasks. For now, you'll focus on creating the model at a high level, which can (and should) be refined as more information becomes available.

Preliminary research found that each process takes 2, 1, and 5 days to complete, respectively, with standard deviations of 0.2, 0.2, and 1 day.

You have built the SimPy model and generators. Time in the model is recorded in days. The following package has been imported for you: import matplotlib.pyplot as plt.

Let's run the model and analyze the results using cluster analysis.

Run the SimPy model stored in a SimPy environment named env for 5 years (assume no leap years).
Create a histogram of the model results stored in record_processes_list with 50 bins.

Exercise

Logistics eCommerce model: Analyzing results

Instructions