simulation n modelling

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Lecture 2

1


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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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simulation n modelling

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