Download VTU (Visvesvaraya Technological University) 8th Semester (Eight Semester) 2020 January 10CS82 System Modeling and Simulation Previous Question Paper
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10CS82
Eighth Semester B.E. Degree Examination, Dec.2019/Jan.2020
System Modeling and Simulation
Time: 3 hrs. Max. Marks:100
Note: Answer FIVE full questions, selecting
at least TWO questions from each part.
PART ? A
1 a. What is simulation? State any three merits and demerits. (05 Marks)
b. Differentiate between continus and discrete system. (05 Marks)
c. A grocery store has one checkt cnter. Customers arrive at this checkt cnter at
random from 1 to 8 minutes apart and each interval time as the same probability of
occurance. The service times vary from 1 to 6 minutes, with probability given below:
Service (minutes) 1 2 3 4 5 6
Probability 0.10 0.20 0.30 0.25 0.10 0.05
Simulate the arrival of six customers and calculate the following:
(i) Average waiting time for a customer.
(ii) Probability that a customer has to wait.
(iii) Probability of a server being Idle.
(iv) Average service time
(v) Average time between arrival.
Use the following sequence of random numbers:
Random digit for arrival : 913, 727, 015, 948, 309

, 922
Random digit for service time : 84, 10, 74, 53, 17
(10 Marks)
2 a. Briefly define any fr concepts used in discrete event simulation. (04 Marks)
b. Generating system snapshots at clock = t and clock = H, explain event scheduling algorithm.
(06 Marks)
c. Suppose the maximum inventory level M is 11 units and the review period N, is 5 days.
Estimate by simulation the average ending units in inventory and number of days when a
shortage condition occurs. The number of units demanded per day is given by the following
distributions. Assume that orders are placed at the close of the business and are received for
inventory at the beginning of business as determined by lead time. Initially simulation
started with 3 units and order of 8 units scheduled to arrive in 2 days of time.
Demand 0 1 2 3 4
Probability 0.10 0.25 0.35 0.21 0.09
Lead time is a random variable, with the following robabilit distribution:
Lead time (days) 1 2
Probability 0.6 0.3 0.1
Random digits for demand : 24, 35, 65, 81, 54, 03, 87, 27, 73, 70, 47, 45, 48, 17, 09
Random digit for lead time : 5, 0, 3 order quantity 9, 11. Simulate for 3 cycles. (10 Marks)
3 a. Differentiate between continus and uniform distributions.
(10 Marks)
b. Briefly explain Poission process.
(10 Marks)
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i
B
1
.L.D.E.
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P. 0. H4LAKATTI
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OLLEGE CP E!1...!EzNEERN
,
*,7!
LIBRAS v N JAPUR.

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7

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1

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:L7.

...:.. ., ;,? ,...;...  .....,..  .4.. 
USN
10CS82
Eighth Semester B.E. Degree Examination, Dec.2019/Jan.2020
System Modeling and Simulation
Time: 3 hrs. Max. Marks:100
Note: Answer FIVE full questions, selecting
at least TWO questions from each part.
PART ? A
1 a. What is simulation? State any three merits and demerits. (05 Marks)
b. Differentiate between continus and discrete system. (05 Marks)
c. A grocery store has one checkt cnter. Customers arrive at this checkt cnter at
random from 1 to 8 minutes apart and each interval time as the same probability of
occurance. The service times vary from 1 to 6 minutes, with probability given below:
Service (minutes) 1 2 3 4 5 6
Probability 0.10 0.20 0.30 0.25 0.10 0.05
Simulate the arrival of six customers and calculate the following:
(i) Average waiting time for a customer.
(ii) Probability that a customer has to wait.
(iii) Probability of a server being Idle.
(iv) Average service time
(v) Average time between arrival.
Use the following sequence of random numbers:
Random digit for arrival : 913, 727, 015, 948, 309

, 922
Random digit for service time : 84, 10, 74, 53, 17
(10 Marks)
2 a. Briefly define any fr concepts used in discrete event simulation. (04 Marks)
b. Generating system snapshots at clock = t and clock = H, explain event scheduling algorithm.
(06 Marks)
c. Suppose the maximum inventory level M is 11 units and the review period N, is 5 days.
Estimate by simulation the average ending units in inventory and number of days when a
shortage condition occurs. The number of units demanded per day is given by the following
distributions. Assume that orders are placed at the close of the business and are received for
inventory at the beginning of business as determined by lead time. Initially simulation
started with 3 units and order of 8 units scheduled to arrive in 2 days of time.
Demand 0 1 2 3 4
Probability 0.10 0.25 0.35 0.21 0.09
Lead time is a random variable, with the following robabilit distribution:
Lead time (days) 1 2
Probability 0.6 0.3 0.1
Random digits for demand : 24, 35, 65, 81, 54, 03, 87, 27, 73, 70, 47, 45, 48, 17, 09
Random digit for lead time : 5, 0, 3 order quantity 9, 11. Simulate for 3 cycles. (10 Marks)
3 a. Differentiate between continus and uniform distributions.
(10 Marks)
b. Briefly explain Poission process.
(10 Marks)
1 of 2
10CS82
a. Explain the characteristics of a queuing system. List different queuing notations. (10 Marks)
b. Suppose that the inter arrival times and service times at a single chair unisexhairstyling
shop have been shown to be exponentially distributed the values of X and 11 are 2 per hr
and 3 per hr respectively that is, the time between arrivals averages i/2 hr, exponentially
distributed and the service time averages 20 minutes, also exponentially distributed. How
server utilization and the probabilities for zero, one, two, three and fr or more customers
in the shop are computed? (10 Marks)
PART ? B
5 a. What are pseudo random numbers? What are the
pseudo random numbers?
b. Generate 6 three digit random numbers using multiplicative
X
o
=117 , a = 43 and M = 1000.
problems that occur while generating
(06 Marks)
congruential method with
(06 Marks)
e.
Five observations of firecrew response times to incoming alarms have been collected to be
used in a simulation investigating possible alternative staffing and crew scheduling policies.
The data are 2.76, 1.83, 0.80, 1.45, 1.24
Develop a preliminary simulation model that uses a response time distribution for five
observations. Thus a method for generating random variates from the response time
distribution is needed. Initially response time X have a range 0 < X < C . If a random number
= 0.71. How it can be represented in graphical view as in Emprical cdf. (08 Marks)
6 a. Explain the need for input modeling and histogram method of identifying the input
distribution. (06 Marks)
b. How chisquare test can be derived from goodnessoffit test? (04 Marks)
c. Briefly explain timeseries input models. (10 Marks)
7 a. Explain stochastic nature of tput data along with measure of performance and their
estimation. (10 Marks)
b. How the tput analysis applied for steady state simulation? Explain any one tput
analysis. (10 Marks)
8 a. How model can be build, perform verification and validation? Explain with diagram.
(10 Marks)
b.
Briefly explain the validation of input t transformation of the model and the varis
techniques used. (10 Marks)
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This post was last modified on 11 April 2020