Reference no: EM13544458
1. Pipeline fluid flows are indicated below. Determine the maximum flow from Node 1 to Node 4.
From
|
To
|
Fluid
|
Node
|
Node
|
Flow
|
1
|
2
|
400
|
2
|
1
|
0
|
1
|
4
|
200
|
4
|
1
|
200
|
1
|
3
|
200
|
3
|
1
|
0
|
2
|
4
|
200
|
4
|
2
|
200
|
3
|
4
|
300
|
4
|
3
|
300
|
(a) 200
(b) 300
(c) 600
(d) 700
(e) none of the above
2. Given the following distances between destination nodes, what is the minimum distance that connects all the nodes?
From
|
To
|
Distance
|
1
|
2
|
200
|
1
|
3
|
300
|
1
|
5
|
400
|
2
|
3
|
300
|
2
|
4
|
400
|
3
|
4
|
200
|
3
|
5
|
200
|
4
|
5
|
100
|
4
|
6
|
300
|
5
|
6
|
400
|
(a) 1000
(b) 800
(c) 700
(d) 1100
(e) none of the above
Table 13-4
|
The following represents a project with known activity times. All times are in weeks.
|
Activity
|
Immediate
Predecessor
|
Time
|
A
|
-
|
4
|
B
|
-
|
3
|
C
|
A
|
2
|
D
|
B
|
7
|
E
|
C, D
|
4
|
F
|
B
|
5
|
G
|
E, F
|
4
|
3. Using the data in Table 13-4, what is the minimum possible time required for completing the project?
(a) 8
(b) 12
(c) 18
(d) 10
(e) none of the above
4. Using the data in Table 13-4, what is the latest possible time that C may be started without delaying completion of the project?
(a) 0
(b) 4
(c) 8
(d) 10
(e) none of the above
5. Using the data in Table 13-4, compute the slack time for activity D.
(a) 0
(b) 5
(c) 3
(d) 6
(e) none of the above
6. Consider a project that has an expected completion time of 50 weeks and a standard deviation of 9 weeks. What is the probability that the project is finished in 57 weeks or fewer? (Round to two decimals.)
(a) 0.68
(b) 0.78
(c) 0.22
(d) 0.32
(e) none of the above
The following table provides information for the next few questions.
Table 13-6
|
Activity
|
Immediate
Predecessor
|
Optimistic
|
Most
Likely
|
Pessimistic
|
Expec-ted t
|
s
|
s2
|
A
|
-
|
2
|
3
|
4
|
3
|
0.333
|
0.111
|
B
|
-
|
2
|
5
|
8
|
5
|
1.000
|
1.000
|
C
|
A
|
1
|
2
|
9
|
3
|
1.330
|
1.780
|
D
|
A
|
5
|
5
|
5
|
5
|
0.000
|
0.000
|
E
|
B, C
|
6
|
7
|
8
|
7
|
0.333
|
0.111
|
F
|
B
|
12
|
12
|
12
|
12
|
0.000
|
0.000
|
G
|
D, E
|
1
|
5
|
9
|
5
|
1.333
|
1.780
|
H
|
G, F
|
1
|
4
|
8
|
4.167
|
1.167
|
1.362
|
7. Which activities are part of the critical path?
(a) A, B, E, G, H
(b) A, C, E, G, H
(c) A, D, G, H
(d) B, F, H
(e) none of the above
8. What is the variance of the critical path?
(a) 5.222
(b) 4.364
(c) 1.362
(d) 5.144
(e) none of the above
Table 14-1
|
M/M/2
|
|
Mean Arrival Rate:
|
9 occurrences per minute
|
Mean Service Rate:
|
7 occurrences per minute
|
Number of Servers:
|
2
|
|
|
Queue Statistics:
|
|
Mean Number of Units in the System:
|
2.191
|
Mean Number of Units in the Queue:
|
0.905
|
|
Mean Time in the System:
|
14.609 minutes
|
Mean Time in the Queue:
|
6.037 minutes
|
Service Facility Utilization Factor:
|
0.643
|
Probability of No Units in System:
|
0.217
|
|
|
|
|
9. According to the information provided in Table 14-1, on average, how many units are in the line?
(a) 0.643
(b) 2.191
(c) 2.307
(d) 0.217
(e) 0.905
10. According to the information provided in Table 14-1, what proportion of time is at least one server busy?
(a) 0.643
(b) 0.905
(c) 0.783
(d) 0.091
(e) none of the above
11. Using the information provided in Table 14-1 and counting each person being served and the people in line, on average, how many people would be in this system?
(a) 0.905
(b) 2.191
(c) 6.037
(d) 14.609
(e) none of the above
12. According to the information provided in Table 14-1, what is the average time spent by a person in this system?
(a) 0.905 minutes
(b) 2.191 minutes
(c) 6.037 minutes
(d) 14.609 minutes
(e) none of the above
13. According to the information provided in Table 14-1, what percentage of the total available service time is being used?
(a) 90.5%
(b) 21.7%
(c) 64.3%
(d) It could be any of the above, depending on other factors.
(e) none of the above
Table 14-5
|
M/D/1
|
|
Mean Arrival Rate:
|
5 occurrences per minute
|
Constant Service Rate:
|
7 occurrences per minute
|
|
|
Queue Statistics:
|
|
Mean Number of Units in the System:
|
1.607
|
Mean Number of Units in the Queue:
|
0.893
|
Mean Time in the System:
|
0.321 minutes
|
Mean Time in the Queue:
|
0.179 minutes
|
Service Facility Utilization Factor:
|
0.714
|
14. According to the information provided in Table 14-5, which presents the solution for a queuing problem with a constant service rate, on average, how much time is spent waiting in line?
(a) 1.607 minutes
(b) 0.714 minutes
(c) 0.179 minutes
(d) 0.893 minutes
(e) none of the above
15. According to the information provided in Table 14-5, which presents the solution for a queuing problem with a constant service rate, on average, how many customers are in the system?
(a) 0.893
(b) 0.714
(c) 1.607
(d) 0.375
(e) none of the above
16. According to the information provided in Table 14-5, which presents a queuing problem solution for a queuing problem with a constant service rate, on average, how many customers arrive per time period?
(a) 5
(b) 7
(c) 1.607
(d) 0.893
(e) none of the above
Table 15-2
|
A pharmacy is considering hiring another pharmacist to better serve customers. To help analyze this situation, records are kept to determine how many customers will arrive in any 10-minute interval. Based on 100 ten-minute intervals, the following probability distribution has been developed and random numbers assigned to each event.
|
|
|
|
Number of Arrivals
|
Probability
|
Interval of Random Numbers
|
6
|
0.2
|
01-20
|
7
|
0.3
|
21-50
|
8
|
0.3
|
51-80
|
9
|
0.1
|
81-90
|
10
|
0.1
|
91-00
|
17. According to Table 15-2, the number of arrivals in any 10-minute period is between 6 and 10, inclusive. Suppose the next three random numbers were 18, 89, and 67, and these were used to simulate arrivals in the next three 10-minute intervals. How many customers would have arrived during this 30-minute time period?
(a) 22
(b) 23
(c) 24
(d) 25
(e) none of the above
18. According to Table 15-2, the number of arrivals in any 10-minute period is between 6 and 10, inclusive. Suppose the next three random numbers were 20, 50, and 79, and these were used to simulate arrivals in the next three 10-minute intervals. How many customers would have arrived during this 30-minute time period?
(a) 18
(b) 19
(c) 20
(d) 21
(e) none of the above
19. According to Table 15-2, the number of arrivals in any 10-minute period is between 6 and 10 inclusive. Suppose the next 3 random numbers were 02, 81, and 18. These numbers are used to simulate arrivals into the pharmacy. What would the average number of arrivals per 10-minute period be based on this set of occurrences?
(a) 6
(b) 7
(c) 8
(d) 9
(e) none of the above
Table 15.3
|
A pawn shop in Arlington, Texas, has a drive-through window to better serve customers. The following tables provide information about the time between arrivals and the service times required at the window on a particularly busy day of the week. All times are in minutes.
|
|
|
|
Time Between Arrivals
|
Probability
|
Interval of Random Numbers
|
1
|
0.1
|
01-10
|
2
|
0.3
|
11-40
|
3
|
0.4
|
41-80
|
4
|
0.2
|
81-00
|
|
|
|
Service Time
|
Probability
|
Interval of Random Numbers
|
1
|
0.2
|
01-20
|
2
|
0.4
|
21-60
|
3
|
0.3
|
61-90
|
4
|
0.1
|
91-00
|
The first random number generated for arrivals is used to tell when the first customer arrives after opening.
|
20. According to Table 15-3, the time between successive arrivals is 1, 2, 3, or 4 minutes. If the store opens at 8:00a.m. and random numbers are used to generate arrivals, what time would the first customer arrive if the first random number were 02?
(a) 8:01
(b) 8:02
(c) 8:03
(d) 8:04
(e) none of the above
21. According to Table 15-3, the time between successive arrivals is 1, 2, 3, or 4 minutes. The store opens at 8:00a.m. and random numbers are used to generate arrivals and service times. The first random number to generate an arrival is 39, while the first service time is generated by the random number 94. What time would the first customer finish transacting business?
(a) 8:03
(b) 8:04
(c) 8:05
(d) 8:06
(e) none of the above
22. According to Table 15-3, the time between successive arrivals is 1, 2, 3, or 4 minutes. The store opens at 8:00a.m. and random numbers are used to generate arrivals and service times. The first 3 random numbers to generate arrivals are 09, 89, and 26. What time does the third customer arrive?
(a) 8:07
(b) 8:08
(c) 8:09
(d) 8:10
(e) none of the above
23. According to Table 15-3, the time between successive arrivals is 1, 2, 3, or 4 minutes. The store opens at 8:00a.m. and random numbers are used to generate arrivals and service times. The first two random numbers for arrivals are 95 and 08. The first two random numbers for service times are 92 and 18. At what time does the second customer finish transacting business?
(a) 8:07
(b) 8:08
(c) 8:09
(d) 8:10
(e) none of the above
Table 15-4
|
|
|
|
Variable Value
|
Probability
|
Cumulative Probability
|
0
|
0.08
|
0.08
|
1
|
0.23
|
0.31
|
2
|
0.32
|
0.63
|
3
|
0.28
|
0.91
|
4
|
0.09
|
1.00
|
|
|
|
Number of Runs
|
200
|
|
Average Value
|
2.10
|
24. According to Table 15-4, which presents a summary of the Monte Carlo output from a simulation of 200 runs, there are 5 possible values for the variable of concern. If this variable represents the number of machine breakdowns during a day, what is the probability that the number of breakdowns is 2 or fewer?
(a) 0.23
(b) 0.31
(c) 0.32
(d) 0.63
(e) none of the above
25. According to Table 15-4, which presents a summary of the Monte Carlo output from a simulation of 200 runs, there are 5 possible values for the variable of concern. If this variable represents the number of machine breakdowns during a day, what is the probability that the number of breakdowns is more than 4?
(a) 0
(b) 0.08
(c) 0.09
(d) 1.00
(e) none of the above
26. According to Table 15-4, which presents a summary of the Monte Carlo output from a simulation of 200 runs, there are 5 possible values for the variable of concern. If this variable represents the number of machine breakdowns during a day, based on this simulation run, what is the average number of breakdowns per day?
(a) 2.00
(b) 2.10
(c) 2.50
(d) 200
(e) none of the above
27) Which of the following represents the primary reason simulation cannot be used for the classic EOQ model?
a) too many parameters involved
b) too many decision variables
c) EOQ models are probabilistic
d) EOQ models are deterministic
e) None of the above
28) Simulation models can be broken down into which of the following three categories?
a) Monte Carlo, queuing, and inventory
b) queuing, inventory, and maintenance policy
c) Monte Carlo, operational gaming, systems simulation
d) inventory, systems simulation, and operational gaming
e) None of the above
28) The logic in a simulation model is presented graphically through which of the following?
a) scatterplot
b) flowchart
c) blueprint
d) decision tree
e) None of the above
30) Markov analysis is a technique that deals with the probabilities of future occurrences by
a) using the simplex solution method.
b) analyzing currently known probabilities.
c) statistical sampling.
d) the minimal spanning tree.
e) None of the above
31) The probability that we will be in a future state, given a current or existing state, is called
a) state probability.
b) prior probability.
c) steady state probability.
d) joint probability.
e) transition probability.
32) A state probability when equilibrium has been reached is called
a) state probability.
b) prior probability.
c) steady state probability.
d) joint probability.
e) transition probability.
33) Occasionally, a state is entered that will not allow going to any other state in the future. This is called
a) status quo.
b) stability dependency.
c) market saturation.
d) incidental mobility.
e) an absorbing state.