simulation n modelling
Transcript of simulation n modelling
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Lecture 2
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System:
a collection of mutually interacting objects
designed to accomplish a goal (machines repair
system) Entities:
denotes an element/object within boundary of
system (machines, operators, repairman)
Entity
work being performed on object Resource performing the work
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Attribute:
Characteristic or property or an entity (machine ID,
Type of breakdown, time that machine went down)
Activity: transforms the state of an object usually over some
time (repair man service time, machine run time)
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State of the system:
Numeric values that contain all the information
necessary to describe the system at any time.
Delays:
Processes that take a conditional length of time in
the system
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Events:
Change the state of the system(end of service of
machine,machine breaks down)
Queue:
it is set, used to model waiting
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Entities
Sets
People waiting at each floor
Attributes
Elevators
People
Elevators, people
capacity, speed, destination, current location of each elevator
inter-arrival time at each floor,
destination of each people
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State of system:
# of people on each elevator
# of people in each floor
Activities Load/Unloading passenger
Travel to next floor (speed and distance)
Persons travel to elevator
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Delays:
Persons waiting for elevator
Events:
Elevator arrival
End unloading
End Loading
Person Arrival
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There are two types of simulation models,
static and dynamic.
Definition: A static simulation model is a
representation of a system at a particular pointin time.
We usually refer to a static simulation as
a Monte Carlo simulation.
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Definition: A dynamic simulation is arepresentation of a system as it evolves overtime.
Within these two classifications, a simulationmay be deterministic or stochastic.
A deterministic simulation model is one thatcontains no random variables;
a stochastic simulation model contains one ormore random variables.
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Discrete event:
state of system changes only at discrete points in
time(events)
ex. Machine repair problem Programming
Look at system only when events occur; time is advanced
from event to event.
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Discrete event:
state of system changes only at discrete points in
time(events)
ex. Machine repair problem Programming
Look at system only when events occur; time is advanced
from event to event.
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Continuous event:
state of system changes continuously over time
Ex. Level of fluid in tank Programming:
Advances time in small intervals. Use differential
equations to represent flows.
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SUBSYSTEM
(At a lower level of details)
Block Building Principle(A series of Blocks)
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And now
Any questions???
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