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Simulation by Sunaina Dubey

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Simulation by Sunaina Dubey

  1. 1. SIMULATION Presented by Sunaina Dubey Mba 3rd sem
  2. 2.  Definition Steps in simulation Singnificance of simulation Techniques of simulation Example –problem of Monte carlo simulation and its solution
  3. 3. “Simulation is the process of designing a model of a real system and conducting experiments with the model for the purpose of understanding the behaviour for the operation of the system”
  4. 4. In general terms simulation involves developing a model of some real phenomenon and then performing an experiment on the model evolved.It is a descriptive and not optimisting techniques.
  5. 5. Steps for simulation Formulation of problemIntroduce important varibles decision rules of system parameters Construct simulation model Validate the model Design experiments Modify the modele by changing the input data Perform simulation Is simulation process is complete? Select the best course of action
  6. 6. 1. Formulation of problem2. Introduce important variables decision rules of system parameters.3. Construct simulation model4. Validate the model5. Design experiments6. Perform simulation7. Is simulation problem is complete8. Select the best course of action
  7. 7.  To solve cumbersome problem Experiment Study the long term effect To best proposed analytical solution Stability Generation of data Time saving Last resort
  8. 8.  Monte carle simulation Simulation and buisness situation Simulation and inventory control Simulation and financial decision
  9. 9.  Steps:-1. Establishing probabilty distribution2. Comulative probability distribution3. Setting random number intervals4. Generating random no
  10. 10. QUE:- Over 100 days period the daily demands of a certain commodity shown the following frquency distribution pattern Daily 0 1 2 3 4 5 demand No. of 10 20 40 20 6 4 Total days 100 Using the given data simulate a ten day sequence of the demands values
  11. 11. Solution:- Daily demand Probabilty=no Cumulative Rendom no of days/total probability assignment no of days 0 10/100=0.10 0.10 00-09 1 20/100=0.20 0.30 10-29 2 40/100=0.40 0.70 30-69 3 20/100=0.20 0.90 70-89 4 6/100=0.06 0.96 90-95 5 4/100=0.04 1.00 96-99 How the random no.assignment has been made is very simple to figure out (on the basis of cumulative frequency)
  12. 12. Day number Generated random Generating demand demands1 67 22 84 33 01 04 77 35 90 46 14 17 15 18 74 39 44 210 77 3 Total=22 Average daily demand =22/10 =2.2 answer
  13. 13. THANK YOU

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