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1 1 Slide Chapter 6 Simulation n Advantages and Disadvantages of Using Simulation n Modeling n Random Variables and Pseudo-Random Numbers n Time Increments.

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Presentation on theme: "1 1 Slide Chapter 6 Simulation n Advantages and Disadvantages of Using Simulation n Modeling n Random Variables and Pseudo-Random Numbers n Time Increments."— Presentation transcript:

1 1 1 Slide Chapter 6 Simulation n Advantages and Disadvantages of Using Simulation n Modeling n Random Variables and Pseudo-Random Numbers n Time Increments n Simulation Languages n Validation and Statistical Considerations n Examples Risk Analysis Risk Analysis Waiting Line Simulation Waiting Line Simulation

2 2 2 Slide What is Simulation? An attempt to duplicate the features, appearance, and characteristics of a real system 1.To imitate a real-world situation mathematically 2.To study its properties and operating characteristics 3.To draw conclusions and make action decisions based on the results of the simulation

3 3 3 Slide Simulation Applications Bus scheduling Design of library operations Taxi, truck, and railroad dispatching Production facility scheduling Plant layout Capital investments Production scheduling Sales forecasting Inventory planning and control Ambulance location and dispatching Assembly-line balancing Parking lot and harbor design Distribution system design Scheduling aircraft Labor-hiring decisions Personnel scheduling Traffic-light timing Voting pattern prediction

4 4 4 Slide Select best course Examine results Conduct simulation Specify values of variables Construct model Introduce variables The Process of Simulation Define problem

5 5 5 Slide Advantages of Simulation 1.Relatively straightforward and flexible 2.Can be used to analyze large and complex real- world situations that cannot be solved by conventional models 3.Real-world complications can be included that most OR models cannot permit 4.“Time compression” is possible

6 6 6 Slide Advantages of Simulation 5.Allows “what-if” types of questions 6.Does not interfere with real-world systems 7.Can study the interactive effects of individual components or variables in order to determine which ones are important

7 7 7 Slide Disadvantages of Simulation 1.Can be very expensive and may take months to develop 2.It is a trial-and-error approach that may produce different solutions in repeated runs 3.Managers must generate all of the conditions and constraints for solutions they want to examine 4.Each simulation model is unique

8 8 8 Slide Monte Carlo Simulation Select numbers randomly from a probability distribution Select numbers randomly from a probability distribution Use these values to observe how a model performs over time Use these values to observe how a model performs over time Random numbers each have an equal likelihood of being selected at random Random numbers each have an equal likelihood of being selected at random

9 9 9 Slide Distribution of Demand LAPTOPS DEMANDED FREQUENCY OF PROBABILITY OF PER WEEK, DEMAND DEMAND, P ( x ) CUMULATIVE 0 20 0.20 0 0 20 0.20 0 1 40 0.40 0.20 1 40 0.40 0.20 2 20 0.20 0.60 2 20 0.20 0.60 3 10 0.10 0.80 3 10 0.10 0.80 4 10 0.10 0.90 4 10 0.10 0.90 100 1.00 100 1.00

10 10 Slide Roulette Wheel of Demand 90 80 60 200 x = 2 x = 0 x = 4 x = 3 x = 1

11 11 Slide Generating Demand from Random Numbers DEMAND,RANGES OF RANDOM NUMBERS, xr 00-19 120-59 r = 39 260-79 380-89 490-99

12 12 Slide Random Number Table 39657645451990696461 73712370906597601211 72184733845167479719 75122569171795217858 37177988746352063430

13 13 Slide 15 Weeks of Demand Average demand = 31/15 = 2.07 laptops/week WEEK r DEMAND ( x )REVENUE (S) 13914,300 27328,600 37228,600 47528,600 53714,300 60200 787312,900 898417,200 91000 104714,300 1193417,200 122114,300 1395417,200 1497417,200 156928,600  = 31$133,300

14 14 Slide Computing Expected Demand E ( x ) = (0.20)(0) + (0.40)(1) + (0.20)(2) + (0.10)(3) + (0.10)(4) = 1.5 laptops per week Not particularly close to simulated result of 2.07 laptops Difference is due to small number of periods analyzed

15 15 Slide Random Numbers in Excel

16 16 Slide Simulation in Excel Enter this formula in G6 and copy to G7:G20 Enter “=4300*G6” in H6 and copy to H7:H20 Generate random numbers for cells F6:F20 with the formula “=RAND()” in F6 and copying to F7:F20 = AVERAGE (G6:G20)

17 17 Slide Simulation in Excel

18 18 Slide Example of Risk Analysis PortaCom Project n n PortCom’s product design group has developed a prototype for a new high-quality portable printer. The new printer has an innovative design and the potential to capture a significant share of the portable printer market. Preliminary marketing and financial analysis have provided the following information. Selling price = $249 per unit Administrative cost = $400,000 Advertising cost = $600,000 n n PortaCom believes that the costs and the demand range as follows: Unit direct labor cost = $43~$47 Unit parts cost = $80~$100 First-year demand = 1500~28,500 units

19 19 Slide Simulation n The advantage of simulation is that it allows us to assess the probability of a profit and the probability of a loss. Procedure of simulation 1. Check parameters 2. Check controllable inputs 3. Check probabilistic inputs * Generate random numbers * Generate random numbers 4. Formulate a model 5. Draw a flowchart

20 20 Slide Simulation 1. Check parameters Selling price = $249 per unit Administrative cost = $400,000 Advertising cost = $600,000 2. Check controllable inputs Whether or not introduce the product 3. Check probabilistic inputs Unit direct labor cost range = $43~$47 Unit parts cost range = $80~$100 First-year demand range = 1500~28,500 units

21 21 Slide Simulation 4. Formulate a model Profit=(249-c1-c2)X-1,000,000 5. Draw a flowchart

22 22 Slide Probability Distribution of the Direct Labor Cost Direct labor cost Probability $43 0.1 $44 0.2 $45 0.4 $46 0.2 $47 0.1

23 23 Slide Probability Distribution of the Parts Costs n n The probability distribution for the parts cost per unit is the uniform distribution as follows:

24 24 Slide Probability Distribution of the First-year Demand n n The first-year demand is described by the normal probability distribution with mean 15,000 units and the standard deviation 45000 units as follows:

25 25 Slide How to Generate Random Numbers n n Computer-generated random numbers * Assign ranges of random numbers to to corresponding values of probabilistic inputs. The prob. of any input value is identical to the prob. of its occurrence in the real system. * Placing =RAND() in a cell of an Excel worksheet will result in a random number.

26 26 Slide Generate Random Value for Direct Labor Cost Interval of Direct labor cost Probability random numbers $43 0.1 0.0~0.1 $44 0.2 0.1~0.3 $45 0.4 0.3~0.7 $46 0.2 0.7~0.9 $47 0.1 0.9~1.0 *Excel Statement =Vlookup(Rand(),range, Col_index)

27 27 Slide Generate Random Numbers for Parts Cost n With a uniform probability distribution, the following relationship between the random number and the associated value of the parts cost is used. Parts cost=a+r(b-a) where r=random number where r=random number a=smallest value for parts cost a=smallest value for parts cost b=largest value for parts cost b=largest value for parts cost Parts cost=80+r(100-80)=80+r20

28 28 Slide Generate Random Numbers for First-year Demand n Because first-year demand is normally distributed, we need a procedure for generating random values from a normal distribution. n We use the following formula of Excell =NORMINV(RAND(),mean,standard deviation)

29 29 Slide Waiting Line Simulation n HKSB Savings Bank will open several new branch bank during the coming year. Each new branch is designed to have one automated teller machine (ATM). A concern is that during busy periods several customer may have to wait to use the ATM. This concern prompted the bank to undertake a study of the waiting line system. The bank’s vise president want to determine whether one ATM will be sufficient. The bank established service guidelines for its ATM system stating that the average customer waiting time for an ATM should be one minute or less

30 30 Slide Waiting Line Simulation n Customer Arrival Times Interval Time = a + r (b-a) r = random number between o and 1 a = minimum interarrival time b = maximum interarrival time For the HKSB ATM System, the minimum interarrival time is a = 0 minutes, and the maximum interarrival time is b = 5 minutes Interval Time = 0 + r (5 - 0)= 5r Interval Time = 0 + r (5 - 0)= 5r

31 31 Slide n Customer Arrival Times For the HKSB ATM System, the minimum interarrival time is a = 0 minutes, and the maximum interarrival time is b = 5 minutes Interval Time = 0 + r (5 - 0)= 5r Interval Time = 0 + r (5 - 0)= 5r Assume that the simulation run begins at time = 0, A random number of r= 0.2804 generates an interval time of 5(0.2804) = 1.4 minutes for customer 1. A second random number of r=0.2598 generates an interarrival time of 5(0.2598) = 1.3 minutes, indicating that customer 2 arrive 1.3 minutes after customer 1. Thus customer 2 arrives 1.4 + 1.3 = 2.7 minutes after the simulation begin. Continuing, a third random number of r = 0.9802 indicates that customer 3 arrives 4.9 minutes after customer 2, which 7,6 minutes after the simulation begin.

32 32 Slide Waiting Line Simulation n HKSB ATM Simulation Model Model Number of ATMs Interarrival Time O perating Character istic Service Time Time Interarrival Times (Uniform Distribution) Smallest Value0 Largest Value5 Service Times (Normal Distribution) Mean2 Std Deviation0.5

33 33 Slide Waiting Line Simulation CustomerInterarrival Time Arrival time Service Start Time Waiting Time Service Time Completion Time Time in System 11.4 0.02.33.72.3 21.32.73.71.01.55.22.5 34.97.6 0.02.29.82.2 43.511.1 0.02.513.62.5 50.711.813.61.8 15.43.6 62.814.615.40.82.417.83.2 72.116.717.81.12.119.93.2 80.617.319.92.61.821.74.4 92.519.821.71.92.023.73.9 101.921.723.72.02.326.04.3 Total21.711.220.9 Averages2.171.122.09 Simulation results for 10 ATM CustomerSimulation results for 10 ATM Customer

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