SOLUTIONS MANUAL for Stochastic Modeling: Analysis and ...

More documents

Recommendations

Info

26 CHAPTER 4. SIMULATION C 2 ← T n+1 + FZ −1 (random()) endif endif C 1 ← T n+1 + FG −1 (random()) e 2 () (finish job) S n+1 ← S n − 1 if {S n+1 > 0} then B n ← FB −1 (random()) if {B n =0} then C 2 ← T n+1 + FX −1 (random()) else C 2 ← T n+1 + FZ −1 (random()) endif endif 4. Let D n represent the number of hamburgers demanded on the nth day. We model D 1 ,D 2 ,... as independent. Let S n represent the number of patties in stock at the beginning of the nth day. Define the following system events with associated clocks: e 0 () (initialization) S 0 ← 1000 C 1 ← 1 e 1 () (morning count) if n is odd then if {S n ≤ 500} then S n+1 ← S n − FD −1 (random()) +(1000 − S n ) else S n+1 ← S n − FD −1 (random()) endif else
27 S n+1 ← S n − FD −1 endif (random()) 5. Let X n represent the time to complete the nth job. Let S n represent the number of jobs in process or waiting in the buffer. Define the following system events and associated clocks: e 0 () (initialization) C 1 ← 30 C 2 ←∞ S 0 ← 0 e 1 () (arrival of a job) S n+1 ← S n +1 if {S n+1 =1} then C 2 ← T n+1 + FX −1 (random()) endif C 1 ← T n+1 +30 e 2 () (finish a job) S n+1 ← S n − 1 if {S n+1 > 0} then C 2 ← T n+1 + FX −1 (random()) endif 6. Let B n be a Bernoulli random variable representing the CPU assignment of the nth job. Let S 0,n represent the number of jobs at CPU A, and S 1,n similar for CPU B. Define the following system events and associated clocks: e 0 () (initialization) S 0,n ← 0 S 1,n ← 0 C 1 ← 40 C 2 ←∞ C 3 ←∞
Page 1 and 2: SOLUTIONS MANUAL for Stochastic Mod
Page 3 and 4: ii CONTENTS
Page 5 and 6: Chapter 2 Sample Paths 1. The simul
Page 7 and 8: 3 7. Inputs: Number of hamburgers d
Page 9 and 10: Chapter 3 Basics 1. (a) Pr{X =4} =
Page 11 and 12: (b) 6. (a) F Y (a) = = ∫ a ⎧
Page 13 and 14: 9 (a) Pr{X 2 =1| X 1 =0} = Pr{X 2 =
Page 15 and 16: 11 16. Let U be a random variable h
Page 17 and 18: 13 Y = ⎧ ⎪⎨ ⎪⎩ 1, 0 ≤ U
Page 19 and 20: 15 (d) E[X] = ∑ all a ap X (a) =0
Page 21 and 22: 17 ( ) ∞∑ d 2 = γ a=1 dq 2 qa+
Page 23 and 24: 19 = ∫ ∞ −∞ ∫ ∞ a 2 f X
Page 25 and 26: 21 (b) Let T ≡ number of trials u
Page 27 and 28: (b) f is maximized at a = β giving
Page 29: Chapter 4 Simulation 1. An estimate
Page 33 and 34: 29 (b) Ȳ 1 = {0(5 − 0) + 1(6 −
Page 35 and 36: Chapter 5 Arrival-Counting Processe
Page 37 and 38: 33 Pr{Y 2,6 > 30} = 1− Pr{Y 2,6
Page 39 and 40: 8. (a) Restricted to periods of the
Page 41 and 42: 37 Pr{Y (A) 1.5 > 1000,Y (B) 1.5 >
Page 43 and 44: 39 Pr{Y (B) 2 − Y (B) 1 > 5,Y (B)
Page 45 and 46: 41 (b) 20. (a) Pr{Y 52 − Y 48 =20
Page 47 and 48: 43 ⎧ ⎪⎨ λ(t) = ⎪⎩ 144, 0
Page 49 and 50: while {b
Page 51 and 52: 27. We suppose that the time to bur
Page 53 and 54: and the latter with rate ( λ ′
Page 55 and 56: Chapter 6 Discrete-Time Processes 1
Page 57 and 58: 53 n =5 ⎛ ⎜ ⎝ 0.00001 0.68645
Page 59 and 60: 55 with ŝe = √ ̂p(1 − ̂p) 45
Page 61 and 62: 57 14. Case 6.3 S n represents the
Page 63 and 64: 59 Pr{≤ 1 defective} = a + b + c
Page 65 and 66: 61 ⎛ P = ⎜ ⎝ 0.92 0.08 0 0 0
Page 67 and 68: 63 25. (a) We first argue that µ 1
Page 69 and 70: 65 The expected number of spins is
Page 71 and 72: 67 = 1− Pr{X 1 >n} Pr{X 2 >n} = 1
Page 73 and 74: 69 = ∑ h∈A Pr{S 1 = j | S 0 = h
Page 75 and 76: 71 Therefore, the long-run expected
Page 77 and 78: 73 31. We show (6.5) for k = 2. The
Page 79 and 80: Chapter 7 Continuous-Time Processes
Page 81 and 82:
77 dp i3 (t) dt dp i4 (t) dt dp i5
Page 83 and 84:
79 endif C 2 ← T n+1 + FH −1 (r
Page 85 and 86:
81 8. See Exercise 7 for an analysi
Page 87 and 88:
y conditioning on the first state v
Page 89 and 90:
85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Page 91 and 92:
87 or λµ 00 = 1 +λµ 10 λµ 01
Page 93 and 94:
89 e 2 () (order arrives from manuf
Page 95 and 96:
91 − λ M ∫ ∞ λ 1 + λ M t =
Page 97 and 98:
Chapter 8 Queueing Processes 1. Let
Page 99 and 100:
95 λ i = µ i = { 20(1 − i/16),
Page 101 and 102:
97 (c) l q = ∞∑ π 2 + (j − 2
Page 103 and 104:
We have assumed a 24-hour day, but
Page 105 and 106:
101 ∑ 20 j=0 d j ≈ 453.388 ⎧
Page 107 and 108:
103 (c) For the M/M/s/c with s ≤
Page 109 and 110:
will be at the front of the queue o
Page 111 and 112:
107 (b) For the M/M/1 For the M/D/1
Page 113 and 114:
109 = (1− ρ 1 )(1 − ρ 2 ) ∞
Page 115 and 116:
111 i a 0i µ (i) 1 20 30 2 0 30 (
Page 117 and 118:
113 or or ⎛ Λ[(I − R) ′ ]
Page 119 and 120:
115 i s i ρ i 1 19 0.88 2 4 0.75 3
Page 121 and 122:
It appears that there will be very
Page 123 and 124:
Chapter 9 Topics in Simulation of S
Page 125 and 126:
9. To obtain a rough-cut model, fir
Page 127 and 128:
123 w q =0.49hours l q = 3.2 trucks
Page 129 and 130:
125 When we fix the initial state,
show all

SOLUTIONS MANUAL for Stochastic Modeling: Analysis and ...

Create successful ePaper yourself

Delete template?

Save as template?