SimPy
Simulation in Python
Robert Ramsdell
Great Lakes Dredge & Dock Company
What is SimPy?
- Discreet Event Simulation - The simulation ticks off time between events defined by processes.
- Process Based - simulates the real-world interaction between active processes (machines, customers, messages), that may or may not compete for limited resources (jobs, clerks, processors).
What is SimPy?
- Provides facilities (Python classes) that model processes and resources
- Provides monitor classes to log and analyze the history of chosen variables during a simulation
Extras
- SimGUI - a basic graphical interface.
- SimPlot - a plotting utility.
- SimulationTrace - to trace the execution of the simulation in detail.
- SimulationStep - Step through the simulation one event at a time.
- SimulationRT - to synchronize the simulation with the wall clock.
Basis of the Simulation
- Processes
- Resources
- Monitors
Basis of the Simulation - Processes
- The active objects of the simulation
- Inherit from the Process Class
- A minimum of one process required for the simulation.
- Requires a single process execution method (PEM) that describes the action of the process. This method must contain at least one yield statement.
- A process must be activated to start it's operation.
Basis of the Simulation - Resources
- Identical, unchanging units that processes require to continue. May represent bottlenecks or queues.
- Created using the Resource class that keeps track of their usage.
- Processes can request resources, possibly waiting until they are available.
- Have built-in capacity to monitor usage during the simulation.
Basis of the Simulation - Monitors
- Monitor the history of a variable as a list of (value, time) pairs.
- Created using the Monitor class.
- The observe method used to log an observation.
- Provides information such as the total, mean, time average, etc for the variable.
- Provides a histogram of the values of the variable.
Example 1 - Mismatched Dredges
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Example 1 - Mismatched Dredges
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Example 1 - The Process
- Initialize as a subclass of Process
class TSHD(Process):
def __init__(self,name, load, unload):
Process.__init__(self,name=name)
...
def go(self):
...
while True:
yield hold,self,self.load #Load the hopper
...
yield request,self,riser #Wait on the riser
Example 1 - The Simulation
initialize()
riser = Resource(1,monitored=True)
Dredges=[TSHD('Dodge Island',250,100),
TSHD('Manhattan Island',250,140)]
Example 1 - The Simulation
for d in Dredges:
activate(d,d.go())
simulate(until=1440*2) #Simulate for 2 days
Example 1 - The Output
Dodge Island 350 Manhattan Island 390 250 Dodge Island unloading, waited 0 min 350 Manhattan Island unloading, waited 100 min ... 2300 Manhattan Island unloading, waited 0 min 2440 Dodge Island unloading, waited 40 min 2690 Manhattan Island unloading, waited 0 min 2830 Dodge Island unloading, waited 40 min Riser in use 60 % Dodge Island waited 130 min, completed 7 Manhattan Island waited 100 min, completed 7 Total Loads: 14
The Manhattan wait is at the start. After that the Dodge does all the waiting.
Each does the same number of loads.
How SimPy Works
Advanced Process Control
riser = Resource(1,monitored=True,qType=PriorityQ) ... yield request,self,riser,self.priority
riser = Resource(1,monitored=True,qType=PriorityQ,preemptable=1) ... yield request,self,riser,self.priority
Advanced Process Control
yield waitevent,self,someevent or yield queueevent,self,someevent
someevent is a SimEvent object
yield waituntil,self,d.disconnecting
d.disconnecting is a function that returns True or False
Advanced Process Control
self.interrupt(victim)
if self.interrupted()==True:
#Do something about the interruption
Example 2 - Preemption
#wait on any higher priority dredges
for d in self.waiton:
if d.status in ['SailLoaded','Turn']:
#The other dredge is coming back, wait until it is
# done pumping out
yield waituntil,self,d.disconnecting
#Request the riser - higher priority will pre-empt lower
yield request,self,riser,self.priority
Test the option of teh more productive Dredge taking priority at the riser.
Example 2 - Other changes
cycleorder = ['SailLight','Pump','Turn','SailLoaded','Connect','Discharge',
'Disconnect']
Randomized cycle times and load sizes. Independent random streams and seeds for each dredge.
self.rand=random.Random(seed)
More sophisticated and flexible simulation.
Example 2 - Results
>HopperSim3.py d 120 Manhattan Island Est cycle: 387.0 Dodge Island Est cycle: 354.0 Manhattan Island: 0 wait, 446 loads, 491523 CY total, 386 min Cycle Dodge Island : 14443 wait, 446 loads, 575450 CY total, 354 min Cycle Total Loads: 892 Total CY: 1066974 in 120 days
This is essentially the same as Example 1. The more productive dredge does all the waiting.
Example 2 - Results
>HopperSim3.py d 120 wait Manhattan Island Est cycle: 387.0 Dodge Island Est cycle: 354.0 Manhattan Island : 7536 wait, 427 loads, 470423 CY total, 386 min Cycle Dodge Island : 6509 wait, 468 loads, 603545 CY total, 354 min Cycle Total Loads: 895 Total CY: 1073969 in 120 days
Here the Manhattan will wait if the Dodge is almost done loading, or nearing the riser.
Wait time shifts to the Manhattan and 3 loads are gained over 120 days.
Example 2 - Results
>HopperSim3.py d 120 wait p Manhattan Island Est cycle: 387.0 Dodge Island Est cycle: 354.0 Manhattan Island : 14049 wait, 409 loads, 450914 CY total, 387 min Cycle Dodge Island : 109 wait, 487 loads, 627973 CY total, 354 min Cycle Total Loads: 896 Total CY: 1078888 in 120 days
Here the Manhattan does all the waiting and 1 more load is gained.
Abusing Processes
class Customer(Process):
...
class FrontDoor(Process):
...
def DoorOpens():
yield hold,self,now()+t
c = Customer()
activate(c,c.goinside())
...