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OR SEMINAR
TOPIC
GENERAL METHOD OF SOLUTION FOR O. R MODEL
AKSHAY S. G
INTRODUCTION
* GENERAL METHODS OF SOLUTION FOR O. R MODELS.
* DIFFERENT TYPES OF METHOD.
METHODS OF SOLUTION FOR O. R MODELS
* ANALYTIC METHODS.
* ITERATIVE METHOD.
* MONIE CARLO TECHNIQUE OF SIMULATION.
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.
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.
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.
THANKS

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OR presentation AKSHAY.pptx

  • 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.