In the growth stage of a product’s life cycle, a typical operations strategy

complete solution correct answer key

1. In the growth stage of a product’s life cycle, a typical operations strategy would  be:

1. 1. Increasing capacity.
   2. Short production runs.
   3. Cost minimization.                                                  

                  d.   Increases in process stability.

1. Which  statement is true?

1. 1. The mission statement precedes analysis of external and

internal factors.

1. 1. Market segments are selected prior to development of the

mission statement.

1. 1. Functional strategy is formulated prior to corporate strategy.
   2. The marketing functional strategy dictates the products and

services that the firm will offer.

1. Product innovation rates are a(an):

1. 1. A goal-based measure.
   2. A corporate goal.
   3. A productivity measure.
   4. An external factor.

1. In decision theory, the three states of nature are:

1. 1. Local, regional, and national.
   2. Low, medium, and high
   3. Short-term, mid-term, and long-term.
   4. Certainty, uncertainty, and risk.

-2-

1. Simple or single-stage decision making models are characterized by:

1. 1. Event nodes.
   2. Decision nodes.
   3. Decision arrows.
   4. Conditional payoff tables or matrices.
   5. Decision “chains”.

1. Under uncertainty, the risk averter  decision criterion is:

1. 1. LaPlace.
   2. Maxi-max.
   3. Expected value.
   4. Maxi-min.

1. When probabilities are assigned to events, the decision maker may use:

1. 1. The pessimistic criterion.
   2. The equally-likely criterion.
   3. The expected opportunity loss criterion.
   4. The optimistic criterion.

1. An advantage of simulation modeling is:

1. 1. It generates an optimal solution to the problem.
   2. It allows the inclusion of real-world complications.
   3. It can be used in similar problem applications with only slight

modifications.

1. 1. It forces managers to identify every single relevant variable within

The  problem.

1. Options in designing simulation models include all except:

1. 1. Repeating-  versus  non-repeating random numbers.
   2. Most versus all relevant variables.
   3. One versus several random number strings.
   4. Time-incrementing versus event-incrementing.

1. Which of the following probability distributions cannot be simulated?

1. 1. normal.         b. poisson.     c.  uniform.    d.  all can be simulated.

11.      The service facility is a combination of:

a.       Arrival rates and service rates.

b.      Servers and customers.

c.       Queue length and queue discipline.

d.      Channels and phases.

12.      In queuing problems, the calling population is either:

a.       Known or unknown.

b.      Finite or infinite.

c.       Single or multi-phased.

d.      Random or scheduled.

13.      A maintenance shop employing one mechanic and servicing 50 machines would be described as a:

a.       Single-channel, priority system.

b.      Multi-channel, infinite calling population system.

c.       Single-channel, finite calling population  system.

d.      Multi-channel, finite calling population system.

14.      The likelihood that a decision-maker would ever receive a return equal to

the expected opportunity loss ( EOL ) when making an actual decision is:

a.       100%

b.      Dependent on the event probabilities.

c.       0%

d.      Dependent on the number of states of nature.

15.      Commonly obtained measures of a queuing system’s performance include:

a.       Average time each customer spends in the system, and the probability

that the service system will be idle.

b.      The average queue length, and the maximum time a customer may spend

in the queue.

c.       Maximum queue length, and the probability of a specific number of

customers in the system.

d.      Average queue length, and the probability that the waiting time will ex-

ceed a specified  period.   

True or False: ( select the one correct response )

16.  Bayes Theorem provides the justification for employing the expected value 

       decision criterion.

TRUE          FALSE

17.  Decision trees are solved by starting in the present and working  into the          

       future.

TRUE          FALSE

18.  In a decision tree, a node  ( ○ ) represents an “event”.

TRUE          FALSE

19.  Combining “randomness” and “long-term event probabilities” results in the

       duplication of  “reality” in simulation modeling.

TRUE          FALSE

20.  Several proposed courses of action may be run simultaneously through a                                                    

             simulation model, so as to save time and expense.

TRUE          FALSE

21. “Lambda” ( λ ) is the Greek character used to denote the average service rate

       in queuing theory.

TRUE          FALSE

22.   In a restaurant, the average time spent in the system is the time between a

        customer’s arrival and departure.

TRUE          FALSE

23.  The most common queuing models assume a service rate that is normally-

       distributed.

TRUE          FALSE

24.  A simulation is  iconic  when the relevant variables of the system being  

       simulated exhibit chance in their behavior.

TRUE          FALSE

25.  Random number intervals are based on cumulative probability distributions.

TRUE          FALSE

26.  Results of simulation experiments with large numbers of trials will generally

       be better than those with fewer trials.

TRUE          FALSE

27.  Given the value of “lambda” ( λ ) , a theoretical frequency distribution for

       system arrivals can be established.

TRUE          FALSE

28.  In queuing problems, the term  reneging  refers to the fact that some

       customers switch queues before receiving service.

TRUE          FALSE

29.  All queuing systems exhibit first-in, first-out queue discipline.

TRUE          FALSE

30.  In queuing theory, the theoretical frequency distribution of system arrivals

       must be statistically identical to the observed distribution of system arrivals.

TRUE          FALSE