Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.

Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

Successfully reported this slideshow.

Like this presentation? Why not share!

No Downloads

Total views

5,614

On SlideShare

0

From Embeds

0

Number of Embeds

4

Shares

0

Downloads

153

Comments

7

Likes

2

No notes for slide

- 1. ROY THOMAS SAM SCARIA SONU SEBASTIAN SHILPA MATHEW AMMU VIJAYAN SIJU JOSE SAJITH P S SCARIA JOSEPH
- 2. 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.
- 3. • 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.
- 4. 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.
- 5. 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.
- 6. 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
- 7. Find solution of complicated mathematical expressions. Difficulties of trial and error experimentation are avoided by these method.
- 8. 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.
- 9. 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.
- 10. 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.
- 11. 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.
- 12. 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.
- 13. 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.
- 14. 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.

No public clipboards found for this slide

Login to see the comments