Deterministic events and processes

Discrete Event Simulation in Python

Diogo Costa (PhD, MSc)

Adjunct Professor, University of Saskatchewan, Canada & CEO of ImpactBLUE-Scientific

Event (or Process) determinism

NOTE: Terms "event" and "process" used interchangeably.

What is event (or process) determinism?

Ability of process to be predicted accurately
Process referred to as "Deterministic"

Why are deterministic processes important?

Natural and human-driven activities are complex
Many interdependent processes and resources
Some processes repeat the same way in every occurrence
Impact on system output can be predicted accurately

Examples of deterministic processes or events

Natural world

Height of ocean tides
Acceleration of objects due to gravity (9.81 m$^2$/s)
Movement of planets in solar system
Speed of sound in air (331.29 m/s)
Speed of light (300,000 km/s)
Freezing of water (at 0 degrees Celsius)

Human-driven or human-initiated

Flow from water tap
Speed of water bottle filling machine
Time coffee machine takes to make a coffee
Heat released by oven at 230 degrees Celsius
Washing machine programmed cycles
Functioning of microwave appliance

Representing deterministic events in discrete-event models

Deterministic processes

Predictable impact on dynamic systems
Well-known duration
Repeat themselves in the same manner

Process duration needs to be accounted for in the simulation time

# Deterministic processes (time in hours)
duration_process_1 = 10
duration_process_2 = 5


while sim_time < total_sim_time:


   # Update simulation time: Process 1
   sim_time += duration_process_1


   # Update simulation time: Process 2
   sim_time += duration_process_2

Representing deterministic events using SimPy

A SimPy implementation of deterministic events:

.timeout()method clocks-in duration of process
- Blind to time units
- Treats time as numbers
- Time units need to be consistent across model

# Deterministic processes
duration_process_1 = 10
duration_process_2 = 5

while True:

   # Update simulation time: Process 1
   env.timeout(duration_process_1)

   # Update simulation time: Process 2
   env.timeout(duration_process_2)

Let's practice!

Discrete Event Simulation in Python