101 ch12

A static simulation model is used in situations where the state of the system affects how the system changes or evolves over time.

False

Computer-generated random numbers are normally distributed over the interval from 0 to 1.

False

Computer-generated random numbers are normally distributed.

False

In a Monte Carlo simulation, each simulation trial is dependent upon the result of a previous trial.

False

One disadvantage of simulation is that it is limited in the variety of probability distributions that can be used in modeling a system.

False

Simulation allows the user to specify certain desired results (for example, profit or service level values), and then the necessary model parameters and operating policies are determined.

False

Simulation is an optimization technique.

False

The parameters of a simulation model are the controllable inputs.

False

Validation determines that the computer procedure is operating as it is intended to operate.

False

Verification is the process of ensuring that the simulation model provides an accurate representation of the real system.

False

A discrete-event simulation reviews the status of the system periodically, whether or not an event occurs.

True

A simulation model provides a convenient experimental laboratory for the real system.

True

Computer-generated random numbers are not technically random.

True

Each simulation run provides only a sample of how the real system will operate.

True

For any waiting line system, (Average number of units in waiting line) = (Total waiting time) divided by (Total time of simulation).

True

In comparing different policies using simulation, one should use the same set of random numbers whenever possible.

True

Simulation is a trial-and-error approach to problem solving.

True

Simulation is an excellent technique to use when a situation is too complicated to use standard analytical procedures.

True

Simulation models that must take into account how the system changes or evolves over time are referred to as dynamic simulation models.

True

The degree of risk is associated with the probability or magnitude of loss.

True

To use Excel to generate a normally distributed random variable, you must know the mean and standard deviation of the distribution and have a random number between 0 and 1.

True

Trials of a simulation show what would happen when values of the probabilistic input change.

True

Using simulation to perform risk analysis is like playing out many what-if scenarios by randomly generating values for the probabilistic inputs.

True

A simulation model uses the mathematical expressions and logical relationships of the a. real system. b. computer model. c. performance measures. d. estimated inferences.

a

Numerical values that appear in the mathematical relationships of a model and are considered known and remain constant over all trials of a simulation are a. parameters. b. probabilistic input. c. controllable input. d. events.

a

The process of generating probabilistic inputs and computing the value of the output is called a. simulation. b. verification. c. validation. d. implementation.

a

Which of the following statements is INCORRECT regarding the disadvantages of simulation? a. Each simulation run only provides a sample of how the real system will operate. b. The summary of the simulation data only provides estimates about the real system. c. The process of developing a simulation model of a complex system can be time-consuming. d. The larger the number of probabilistic inputs a system has, the less likely a simulation will provide the best approach for studying the system.

d

A simulation model used in situations where the state of the system at one point in time does not affect the state of the system at future points in time is called a a. dynamic simulation model. b. static simulation model. c. steady-state simulation model. d. discrete-event simulation model.

b

A value for probabilistic input from a discrete probability distribution a. is the value given by the RAND() function. b. is given by matching the probabilistic input with an interval of random numbers. c. is between 0 and 1. d. must be non-negative.

b

In order to verify a simulation model a. compare results from several simulation languages. b. be sure that the procedures for calculations are logically correct. c. confirm that the model accurately represents the real system. d. run the model long enough to overcome initial start-up results.

b

Which of the following statements is INCORRECT regarding the advantages of simulation? a. Simulation is relatively easy to explain and understand. b. Simulation guarantees an optimal solution. c. Simulation models are flexible. d. A simulation model provides a convenient experimental laboratory for the real system.

b

A graphical tool that helps describe the logic of the simulation model is a a. Gantt chart. b. histogram. c. flowchart. d. stem-and-leaf display.

c

A quantity that is difficult to measure with certainty is called a a. risk analysis. b. project determinant. c. probabilistic input. d. profit/loss process.

c

Common features of simulations--generating values from probability distributions, maintaining records, recording data and summarizing results--led to the development of a. Excel and Lotus. b. BASIC, FORTRAN, PASCAL, and C. c. GPSS, SIMSCRIPT, SLAM, and Arena d. LINDO and The Management Scientist

c

The process of determining that the computer procedure that performs the simulation calculations is logically correct is called a. implementation. b. validation. c. verification. d. repetition.

c

Values for the probabilistic inputs to a simulation a. are selected by the decision maker. b. are controlled by the decision maker. c. are randomly generated based on historical information. d. are calculated by fixed mathematical formulas.

c

A table of uniformly distributed random numbers should be read a. from left to right. b. from top to bottom. c. diagonally, starting from the top left corner and moving to the bottom right. d. in any consistent sequence.

d

If customer 2 has a service time of 1.6, and if customer 3 has an interarrival time of 1.1 and a service time of 2.3, when will customer 3's service be completed? a. 5.0 b. 3.9 c. 3.4 d. There is not enough information to answer.

d

Simulation a. does not guarantee optimality. b. is flexible and does not require the assumptions of theoretical models. c. allows testing of the system without affecting the real system. d. All of the alternatives are correct.

d

The number of units expected to be sold is uniformly distributed between 300 and 500. If r is a random number between 0 and 1, then the proper expression for sales is a. 200(r) b. r + 300 c. 300 + 500(r) d. 300 + r(200)

d

The word "uniform" in the term "uniform random numbers" means a. all the numbers have the same number of digits. b. if one number is, say, 10 units above the mean, the next number will be 10 units below the mean. c. all the numbers are odd or all are even. d. each number has an equal probability of being drawn.

d

When events occur at discrete points in time a. a simulation clock is required. b. the simulation advances to the next event. c. the model is a discrete-event simulation. d. All of the alternatives are correct.

d