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Module C10 Simulation of Inventory/Queuing Models – PowerPoint PPT presentation

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Title: Module%20C10


1
Module C10
  • Simulation of Inventory/Queuing Models

2
INVENTORY SIMULATIONS
  • Daily demand for refrigerators at Hotpoint City
    has a probability distribution
  • Lead time is not fixed but has a probability
    distribution
  • Customers who arrive and find Hotpoint out of
    stock will shop elsewhere and Hotpoint will lose
    the sale
  • These conditions do not meet the restrictions of
    inventory models developed earlier

3
Simulation Approach
  • Simulation cannot determine the best inventory
    policy
  • But it can compare policies
  • Compare the following
  • Reordering 10 when supply reaches 6 or less
  • Reordering 12 when supply reaches 3 or less

4
Hotpoint Input Data
  • Current inventory 10
  • Holding costs 2/refrigerator/day
  • Order costs 50 per order
  • Shortage costs 30 per occurrence (sale is
    lost)
  • Demand/day Prob Lead Time
    Prob
  • 0 .08 0 days .05
  • 1 .37 1 day .55
  • 2 .33 2 days .30
  • 3 .17 3 days .10
  • 4 .05

5
RANDOM NUMBER MAPPINGS
  • DAILY DEMAND -- Use column 2
  • 0 1 2 3 4
  • PROB .08 .37 .33 .17 .05
  • RN 00-07 08-44 45-77 78-94 95-99
  • LEAD TIME (DAYS) -- Use column 14
  • 0 1 2 3
  • PROB .05 .55 .30 .10
  • RN 00-04 05-59 60-89 90-99

6
SIMULATION OF Q 10 r 6
  • COSTS
  • DAY BI RN DEM EI LOST ORDER RN LT
    ORD HOLD SHORT
  • 1 10 33 1 9 ---
    --- --- --- --- 18
    ---
  • 2 9 98 4 5 ---
    YES 24 1 50 10
    ---
  • 3 5 26 1 4 ---
    --- --- 0 --- 8
    ---
  • 4 14 91 3 11 ---
    --- --- --- --- 22
    ---
  • 5 11 96 4 7 ---
    --- --- --- --- 14
    ---
  • 6 7 48 2 5 ---
    YES 63 2 50 10
    ---
  • 7 5 82 3 2 ---
    --- --- 1 --- 4
    ---
  • 8 2 27 1 1 ---
    --- --- 0 --- 2
    ---
  • 9 11 96 4 7 ---
    --- --- --- --- 14
    ---
  • 10 7 46 2 5 --- YES
    99 3 50 10 ---
  • 150 112 0
  • Based on this one 10-day simulation average daily
    cost 26.20

7
SIMULATION OF Q 12 r 3
  • COSTS
  • DAY BI RN DEM EI LOST ORDER RN LT
    ORD HOLD SHORT
  • 1 10 33 1 9 ---
    --- --- --- --- 18
    ---
  • 2 9 98 4 5 ---
    --- --- --- --- 10
    ---
  • 3 5 26 1 4 ---
    --- --- --- --- 8
    ---
  • 4 4 91 3 1 ---
    YES 37 1 50 2
    ---
  • 5 1 96 4 0 3
    --- --- 0 ---- 0
    90
  • 6 12 48 2 10 ---
    --- --- --- --- 20
    ---
  • 7 10 82 3 7 ---
    --- --- --- --- 14
    ---
  • 8 7 27 1 6 ---
    --- --- --- --- 12
    ---
  • 9 6 96 4 2 ---
    YES 84 2 50 4
    ---
  • 10 2 46 2 0 ---
    --- --- --- --- 0
    ---
  • 100 88 90
  • Based on this one 10-day simulation average daily
    cost 27.80
  • THE OTHER POLICY APPEARS BETTER

8
QUEUING SIMULATIONS
  • The arrival pattern to a bank is not Poisson
  • There are three clerks with different service
    rates
  • A customer must choose which idle server to go to
  • These conditions do not meet the restrictions of
    queuing models developed earlier

9
TIME BETWEEN ARRIVALS
  • MINUTES PROB RN
  • 1 .40 00-39
  • 2 .30 40-69
  • 3 .20 70-89
  • 4 .10 90-99

10
SERVICE TIME FOR ANN
  • MINUTES PROB RN
  • 3 .10 00-09
  • 4 .20 10-29
  • 5 .35 30-64
  • 6 .15 65-79
  • 7 .10 80-89
  • 8 .05 90-94
  • 9 .05 95-99

11
SERVICE TIME FOR BOB
  • MINUTES PROB RN
  • 2 .05 00-04
  • 3 .10 05-14
  • 4 .15 15-29
  • 5 .20 30-49
  • 6 .20 50-69
  • 7 .15 70-84
  • 8 .10 85-94
  • 9 .05 95-99

12
SERVICE TIME FOR CARL
  • MINUTES PROB RN
  • 6 .25 00-24
  • 7 .50 25-74
  • 8 .25 75-99

13
CHOICE OF SERVER
  • ALL THREE SERVERS IDLE
  • CHOICE PROB RN
  • ANN 1/3 0000-3332
  • BOB 1/3 3333-6665
  • CARL 1/3 6666-9999
  • ( Carls prob. is .0001 more than 1/3)
  • TWO SERVERS IDLE (A/B), (A/C), (B,C)
  • CHOICE A/B A/C B/C PROB RN
  • Ann Ann Bob 1/2 0-4
  • Bob Carl Carl 1/2 5-9

14
ARBITRARY CHOICE OFCOLUMNS FOR SIMULATION
  • EVENT COLUMN
  • ARRIVALS 10
  • CHOICE OF SERVER 15
  • ANNS SERVICE 1
  • BOBS SERVICE 2
  • CARLS SERVICE 3

15
DESIRED QUANTITIES
  • Wq -- the average waiting time in queue
  • W -- the average waiting time in system
  • Lq -- the average customers in the queue
  • L -- the average customers in the system
  • If we get estimates for Wq and W, then we
    estimate
  • Lq ? Wq
  • L ? W

16
WILL WE REACH STEADY STATE?
  • Average time between arrivals 1/?
  • .4(1) .3(2) .2(3) .1(4) 2.0 minutes
  • ? 60/2 30/hr.
  • Anns average service time 1/?A
  • .1(3) .2(4) .05(9) 5.3 minutes
  • ?A 60/5.3 11.32/hr.

17
WILL WE REACH STEADY STATE?
  • Bobs average service time 1/?B
  • .05(2) .1(3) .05(9) 5.5 minutes
  • ?B 60/5.5 10.91/hr.
  • Carls average service time 1/?C
  • .25(6) .50(7) .25(8) 7 minutes
  • ?C 60/7 8.57/hr.
  • ? 30/hr.
  • ?A ?B ?C 11.32 10.91 8.57 30.8/hr.
  • ? lt ?A ?B ?C gt Steady State will be reached

18
THE SIMULATION
  • RN IAT AT Wq RN SERV SB RN ST SE W
  • 1 36 1 801 0 4231 B 801 33
    5 806 5
  • 2 52 2 803 0 7 C 803 98
    8 811 8
  • 3 99 4 807 0 9 B 807 26
    4 811 4
  • 4 54 2 809 0 ------ A 809 88
    7 816 7
  • 5 96 4 813 0 8 C 813 00
    6 819 6
  • 6 20 1 814 0 ------ B 814 48
    5 819 5
  • 7 41 2 816 0 ------ A 816 11
    4 820 4
  • 8 31 1 817 2 6 C 819 61
    7 826 9
  • 9 33 1 818 1 ------ B 819 96
    9 828 10

19
SIMULATION (CONTD)
  • RN IAT AT Wq RN SERV SB RN ST SE W
  • 10 07 1 819 1 ------ A 820 62
    5 825 6
  • 11 21 1 820 5 ------ A 825 54
    5 830 10
  • 12 01 1 821 5 ------ C 826 49
    7 833 12
  • 13 20 1 822 6 ------ B 828 84
    7 835 13
  • 14 18 1 823 7 ------ A 830 69
    6 836 13
  • 15 92 4 827 6 ------ C 833 95
    8 841 14
  • 16 10 1 828 7 ------ B 835 63
    6 841 13
  • 17 90 4 832 4 ------ A 836 31
    5 841 9
  • 18 66 2 834 7 3711 B 841 05
    3 844 10

20
CALCULATING THE STEADY STATE QUANTITIES
  • The quantities we want are steady state
    quantities --
  • The system must be allowed to settle down to
    steady state
  • Throw out the results from the first n customers
  • Here we use n 8
  • Average the results of the rest
  • Here we average the results of customers 9 -18

21
THE CALCULATIONS FOR W, Wq
  • Total Wait in the queue of the last 10 customers
    (1155676747) 49 min.
  • Wq ? 49/10 4.9 min.
  • Total Wait in the queue of the last 10 customers
    (106101213131413910) 90 min.
  • W? 90/10 9.0 min.

22
THE CALCULATIONS FOR L, Lq
  • Lq ?Wq and L ?W
  • ? and W and Wq must be in the same time units
  • ? 30/hr. .5/min.
  • Lq ?Wq ? (.5)(4.9) 2.45
  • L ?W ? (.5)(9.0) 4.5

23
Module C10 Review
  • Simulation of Inventory Models
  • Determine System Parameters
  • Simulate Cost
  • Replicate Experiment or Longer Simulation for
    better results
  • Simulation of Queuing Models
  • Determine System Parameters
  • Check to See if Steady State Will Be Reached
  • Simulate to get WQ and W
  • Use Littles Laws to get L, LQ
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