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SOLUTIONS MANUAL for Stochastic Modeling: Analysis and ...

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81<br />

8. See Exercise 7 <strong>for</strong> an analysis of the (3,7) policy.<br />

For the (2,7) policy<br />

⎛<br />

G =<br />

⎜<br />

⎝<br />

−1/2 0 0 0 0 1/2 0 0<br />

1 −3/2 0 0 0 0 1/2 0<br />

0 1 −3/2 0 0 0 0 1/2<br />

0 0 1 −3/2 0 0 0 0<br />

0 0 0 1 −1 0 0 0<br />

0 0 0 0 1 −1 0 0<br />

0 0 0 0 0 1 −1 0<br />

0 0 0 0 0 0 1 −1<br />

⎞<br />

⎟<br />

⎠<br />

⎛<br />

π =<br />

⎜<br />

⎝<br />

0.2394366197<br />

0.05633802817<br />

0.08450704225<br />

0.1267605634<br />

0.1901408451<br />

0.1901408451<br />

0.07042253521<br />

0.04225352113<br />

⎞<br />

⎟<br />

⎠<br />

λπ 0 ≈ 0.239<br />

∑ 7j=0<br />

jπ j ≈ 3.03<br />

There<strong>for</strong>e, (2,7) carries a slightly lower inventory level but with more than double the<br />

lost sales rate.<br />

9. To solve this problem we must evaluate p 02 (t) <strong>for</strong>t = 17520 hours (2 years). Using<br />

the uni<strong>for</strong>mization approach with n ∗ = 1000, <strong>and</strong> carrying 10 digits of accuracy in all<br />

calculations,<br />

˜p 02 (t) =0.56<br />

with truncation error ≤ 0.72 × 10 −8 .<br />

The reason that this is dramatically larger than the simulation estimate of 0.02 obtained<br />

in Chapter 4 is the difference in repair-time distribution. In Chapter 4 the distribution<br />

is uni<strong>for</strong>m on [4, 48] hours. Here the distribution is exponential on [0, ∞) hours.The<br />

exponential model is pessimistic because it allows repair times longer than 48 hours.<br />

10. Let M = {0, 1, 2} represent the number of failed machines, so that {Y t ; t ≥ 0} is the<br />

number of failed machines at time t hours. When {Y t =0}, the failure rate is 2(0.01),<br />

since each machine fails at rate 0.01/hour <strong>and</strong> there are two machines. When {Y t =1}

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