Developing a discrete-event model

You have been asked to develop a discrete-event model for a farming operation to help allocate resources, increase productivity and identify-eliminate bottlenecks.

You are still discussing the different processes involved with your colleagues and in what detail they should be represented in the model. Thus, you have agreed that the information will be compiled in a dictionary named process_dict with the following structure. The idea is that this dictionary will be updated as more information about the processes becomes available.

process_dict = {
    "Process name 1":  <duration>,
    "Process name 2":  <duration>,
    ...
}

Let's build a generic discrete event model named discrete_model_farm() that can schedule any number of discrete events defined in the dictionary.

The input arguments of the model are (in order):

process_dict: Dictionary with information about the processes
simulation_time: Simulation period

Time in the model will be measured in days.

Initiate the state variables of the model, time and supply_chain (this one records the number of cycles complete) and set them to zero.
Define the while-loop with an ending condition so the model runs while time < simulation_time.
Complete the code to determine the duration of process p that is stored in the process dictionary process_dict.
Add the duration of the process to the state-variable time.

Exercise

Developing a discrete-event model

Instructions