2.  ROY THOMAS
 SAM SCARIA
 SONU SEBASTIAN
 SHILPA MATHEW
 AMMU VIJAYAN
 SIJU JOSE
 SAJITH P S
 SCARIA JOSEPH

3. The process of designing a mathematical or
logical model of a real-system and then
conducting computer-based experiments
with the model to describe, explain, and
predict the behavior of the real system.

5. • Monte carlo method is a substitution for
the mathematical evaluation of a model.
• Darker and Kac define monte carlo
method as combination of probability
methods & sampling techniques providing
solution to complicated partial or integral
differential equation.
• In short, monte carlo technique is
concerned with experiments on random
numbers & it provides solutions to
complicated OR problems.

6.  Where one is dealing with a problem which has not
yet arisen.
 Where the mathematical and statistical problems
are too complicated and some alternative methods
are needed.
 To estimate parameters to a model.

7. Steps of Monte Carlo method
 A Flow diagram is drawn.
 Then correct sample observations are taken to
select some suitable model for the system.
 Then the Probability distribution is converted to
cumulative distribution function.

8.  Sequence of random numbers is selected .
 Sequence of values of the variables of our interest
is determined with the sequence of random
numbers obtained.
 Some standard mathematical functions is applied
to the sequence of values obtained

9.  Find solution of complicated mathematical
expressions.
 Difficulties of trial and error experimentation
are avoided by these method.

10.  These are costly way of getting a solution of
any problem.
 These method do not provide optimal answer
to the problems. The answers are good only
when the size of the sample is sufficiently
large.

11.  It is applied to a wide diversity of problems
such as queuing problems, inventory
problems, risk analysis concerning a major
capital investment.
 It is very useful in budgeting.

12.  Under this method operating environment is
produced and systems allows for analysing
the response from the environment to
alternative management actions.
 The method is complicated and costly.

13.  Random numbers
It is a number in a sequence of numbers
whose probability of occurrence is same as
that of any other number in that sequence.

14.  Pseudo-random Numbers:
Random numbers are called pseudo random
numbers when they are generated by some
deterministic process. But they qualify the pre
determined statistical test for randomness.

15.  For solving simulation problems, there is the
need of generating a sequence of random
numbers.
 Random numbers may be found by
computer ,by random tables, manually etc.

16.  Most common method to obtain random numbers is
to generate them by a computer programme.
 These numbers lie between 0 and 1,in conjunction
with the cumulative probability distribution of a
random variable including 0 but not 1.