OPERATION RESEARCH

1. OR SEMINAR
TOPIC
GENERAL METHOD OF SOLUTION FOR O. R MODEL
AKSHAY S. G

2. INTRODUCTION
* GENERAL METHODS OF SOLUTION FOR O. R MODELS.
* DIFFERENT TYPES OF METHOD.

3. METHODS OF SOLUTION FOR O. R MODELS
* ANALYTIC METHODS.
* ITERATIVE METHOD.
* MONIE CARLO TECHNIQUE OF SIMULATION.

4. ANALYTIC METHODS
* IN THESE METHOD ALL THE TOOLS OF CLASSICAL MATHEMATICS SUCH AS
DIFFERENT CALCULUS AND FINITE DIFFERENCE ARE AVAILABLE FOR THE
SOLUTION OF A MODEL.
* VARIOUS INVENTORY MODELS ARE SOLVED BY THE USE OF THE ANALYTIC
METHOD.

5. ITERATIVE METHOD
* WHENEVER THE CLASSICAL METHODS FAIL, WE USE ITERATIVE PROCEDURE. THE CLASSICAL
METHID MAY FAIL BECAUSE OF THE COMPLEXITY OF THE CONSTRAINTS OR OF THE NUMBER OF
VARIABLES.
* IN THIS PROCEDURE WE START WITH A TRAIL SOLUTION AND A SET OF RULES FOR IMPROVING IT.
THE TRAIL SOLUTION IS IMPROVER BY THE GIVEN RULES AND IS THEN REPLACEE BY THIS IMPROVED
SOLUTION.
* THEVPROCESS OF IMPROVEMENT IS REPEAT UNTIL EITHER NO FUTHER IMPROVEMENT POSSIBLE
OR THE COST OF FURTHER CALCULATION CANNOT BE JUSTIFIED.

6. MONTE CARLO TECHNIQUE OF SIMULATION
* THE BASIC OF MONTE CARLO TECHNIQUE IS RANDOM SAMPLING OF A VARIABLES POSSIBLE
VALUES.
* FOR THIS TECHNIQUE, SOME RANDOM NUMBERS ARE REQUIRED WHICH MAY BE CONVERTED
INTO RANDIM VARIATES WHOSE BEHAVIOR IS KNOWN FROM PAST EXPERIENCE.
* IN SHORT, MONTE CARLO TECHNIQUE IS CONCERNED WITH EXPERIMENT ON RANDOM
NUMBERS AND IT PROVIDES SOLUTIONS TO COMPLICATED O. R PROBLEMS.

7. THANKS