QM FINAL

A standard recursive relation can be developed for all DP problems.

False

A steady state of a Markov Chain depends on the transition probabilities and the initial condition of the system.

False

All assignment problems can be expressed as transportation problems and vice versa.

False

In DP, a "local" decision must be "optimal" to the stage state so that the final solution is "optimal" to the whole problem.

False

In a service system, it is impossible to have long average waiting lines and underutilization of the server at the same time.

False

In computer simulation, a prefect representation of the real system that is of interest is a primary requirement.

False

In goal programming (GP), several goals appear as constraints while the most important one is to be minimized (maximized).

False

Markov analysis is primarily used to make a series decisions over certain time periods.

False

Markov analysis will determine the optimal state and time for a system throughout future periods.

False

The transition probabilities are assumed to be time-dependent.

False

The validation of a simulation model is to ensure that the model will generate an accurate results.

False

The verification of a simulation model is to ensure that the model will describe the system behavior that similar to what is of interested.

False

A basic assumption in assignment problem is that all assignments must be made on one-to-one basis.

True

A basic assumption in transportation problem is that no transshipment between any two sources or destinations is allowed.

True

A simulation model is created to represent something that is typically dynamic and stochastic in nature.

True

A steady state of a Markov Chain is reached when the switch-in equal switch-off for all states.

True

A transportation problem can also be formulated and solved by LP.

True

An "absorbing" state is a state for which there are only switch-ins but no switch-offs.

True

An important characteristic of dynamic programming (DP) is its backward approach.

True

As long as the server in a queuing system desires to be nearly fully utilized, there will be relatively long wait lines.

True

DSS software has been developed to fit the needs of an industry, an organizational function, and/or a particular product.

True

Expert system is an applied branch of artificial intelligence.

True

Expert systems imitate the reasoning process of experts.

True

GP provides a satisfactory solution rather than an optimal one.

True

If service rate is less than arrival rate, an explosive queue will form.

True

In GP, deviation variables may either be desirable or undesirable depending on the nature of the goals.

True

Key management issue to the waiting line problem is a trade-off decision, comparing extra cost of providing more rapid service with costs of waiting.

True

Monte Carlo simulation models can be used only if the probabilities of the outcomes of different actions are known.

True

Recursive relation is a key to link all stages in DP.

True

Simulation can provide answers to "What if" Questions.

True

Startup conditions occur when it is necessary to wait until the model stabilizes to some degree before collecting simulation data.

True

The DP solution usually provides an automatic sensitivity analysis.

True

The Exponential Distribution describes the time between occurrences such as the time between arrivals at a service counter.

True

The experimental design is an important step in simulation to ensure the validity of the study.

True

The main limitation on the application of queuing models is that actual distributions of service times and arrival times may not fit known standard distributions.

True

The transient probabilities are constant in a Markov Chain.

True

With constant arrival and service rates at a service counter, it is possible to have full utilization of the server and zero wait time for the customer.

True

With random arrival and service rates in a waiting line, it is impossible to have full utilization of the server and zero wait time for the customer.

True

67. Cost-benefit analysis for DSS is: a. difficult to calculate because many of the benefits are intangible b. capable of being standardized for standard procedures c. as same as in other MS models (e.g. EOQ) d. all of the above

a. difficult to calculate because many of the benefits are intangible

Which of the following is not a characteristic of Monte Carlo simulation? a. it deals with deterministic situations b. it uses random numbers c. it involves sampling the probability distribution d. it is usually worked out by computers

a. it deals with deterministic situations

The Markov model is used basically for: a. making predictions b. finding optimal solutions c. generating transition matrices d. optimally allocating resources

a. making predictions

Students arrive at the School of Business and Public Administration advising office at the rate of 20 per hour. Judy Gumshoes advises students at the rate of 24 per hour. Both rates follow a Poisson Distribution. What percent of the time is Judy busy with advising? a. .833 b. .890 c. .913 d. .980

b. .890

Students arrive at a class registration room at the Poisson rate of 4 per hour. The officer serves students by FCFS with an average exponentially time of 10 minutes. Which of the following is the mean number of students waiting in line for service? a. 1.0 b. 1.33 c. 2.0 d. 3.2

b. 1.33

Which of the following have servers which are fully (100%) utilized? I. λ = 30, µ = 20 both follow a Poisson Distribution II. λ = 20, µ = 20 both follow a Poisson Distribution III. λ = 10, µ = 20 both follow a Poisson Distribution IV. λ = 20, µ = 20 both are constant, that is not random a. I, II and III only. b. I, II and IV only. c. I, III, and IV only. d. II, III, and IV only.

b. I, II and IV only.

Which of the following is not an advantage of GP over LP? a. It permits analysis of a problem with multiple, conflicting goals. b. It permits consideration of non-feasible solutions. c. It requires explicit priorities of goals. d. It permits tradeoffs among various goals.

b. It permits consideration of non-feasible solutions.

In a single channel queuing system, the queue length will keep growing if: a. average waiting time in the system is larger than the average service time b. average rate of arrival is equal to the average rate of service c. service facility is idle at any time d. none of the above

b. average rate of arrival is equal to the average rate of service

Which of the following is not a DSS characteristic? a. deal with semi-structured problems b. replace managerial judgment c. incorporate data and models d. improve effectiveness rather than efficiency

b. replace managerial judgment

Which of the following is not an input variable in queuing models? a. the mean arrival rate b. the median of arriving customers c. the mean service rate d. the number of servers

b. the median of arriving customers

The steady state probability in a Markov Chain depend only on: a. the initial conditions b. the transition probabilities c. the states of nature d. the number of stages

b. the transition probabilities

Which of the following is/are assumption(s) of the transportation model? a. Unit shipping costs per unit are constant. b. No transshipment is allowed between sources or between destinations. c. (a) and (b) d. none of above

c. (a) and (b)

Students arrive at a single computer terminal during on-line registration at the rate of 10 per hour. On average, the operator of terminal can process 20 per hour. Both rates follow a Poisson Distribution. What is the average waiting time for students before they can sit with the operator? a. 6 minutes b. 5 minutes c. 3 minutes d. 1.2 minutes

c. 3 minutes

Advantages of simulation include all of the following except: a. Model development leads to a better understanding of the real system. b . Even an optimal answer will not result, a good answer will. c. Models are so powerful that they often can replace human expertise. d. A more realistic replication of a system than a mathematical analysis.

c. Models are so powerful that they often can replace human expertise.

Which of the following is not an advantage of dynamic programming? a. It can deal with decision-making under risk. b. It can solve a sequence interrelated decision problems. c. There is no need to investigate all possible solutions. d. The larger the problem, the more efficient is the procedure. e. none of the above.

c. There is no need to investigate all possible solutions

The cost of providing service: a. increases with the service level while the waiting time goes up b. decreases with the service level while the waiting time goes up c. increases with the service level while the waiting time declines d. decreases with the service level while the waiting time declines

c. increases with the service level while the waiting time declines

The principle of optimality in DP implies that the optimal policy for the remaining states depends only upon: a. the initial state. b. the previous stage and the transition matrix. c. the state of the current stage. d. the initial state and the current state.

c. the state of the current stage

Which of the following is/are the most common management objective in making decisions about a queuing system? a. cost minimization b. a specified service level c. profit maximization d. All of the above

d. All of the above

Simulation variables can be classified as: a. managed vs. unmanaged b. internal vs. external c. dependent vs. independent d. all of above

d. all of above

Which of the following is not a benefit of DSS? a. facilitate communication b. objective analysis, use of models c. flexibility and what-if analysis d. all of above

d. all of above

Which of the following is/are components of an expert system? a. knowledge base b. inference engine c. model base d. all of above

d. all of above

A plant-warehouse shipment problem can basically be formulated by: a. transportation. b. linear programming. c. integer programming d. all of the above.

d. all of the above

Initial conditions are important because they are needed to compute: a. the steady state b. the market share after given number of periods c. the transition probabilities (matrix) d. all of the above

d. all of the above

Transportation problems deal with: a. shipments from a number of sources to a number of destinations. b. each source has a fixed capacity c. each destination has a given demand requirement d. all of the above.

d. all of the above

Which of the following are the information generated by the Markov analysis? a. the steady state probabilities b. the transient (state) probabilities c. the chance of system being at a specific state in any given period d. all of the above

d. all of the above

Which of the following describe "what if" analysis? a. it is a type of sensitivity analysis b. it improves confidence in a model c. it increases the rate of application of quantitative analysis d. all of the above

d. all of the above

Validation of a simulation model deals with: a. establishing the sample size b. determining random numbers c. sensitivity of the solution d. none of the above

d. none of the above

Which of the following is not a component of the basic queuing model? a. the arrival process b. the waiting line c. the service discipline d. none of the above

d. none of the above

Which one of the following situations has no waiting? a. λ = 30, µ = 20 both follow a Poisson Distribution b. λ = 20, µ = 20 both follow a Poisson Distribution c. λ = 10, µ = 20 both follow a Poisson Distribution d. λ = 20, µ = 20 both are constant, that is not random

d. λ = 20, µ = 20 both are constant, that is not random

Which of the following steps is/are a part of the Monte Carlo process: a. construct a cumulative distribution b. assign a range of random numbers c. select a random number d. project a corresponding random observation e. all of above

e. all of above

Which of the following is/are components of a DSS? a. database b. model base c. hardware d. user-system interface e. all of the above

e. all of the above