In the long run, the state probabilities become 0 and 1
In no case
In same cases
In all cases
Cannot say
While calculating equilibrium probabilities for a Markov process, it is assumed that
There is a single absorbing state
Transition probabilities do not change
There is a single non-absorbing state
None of the above
The first order Markov chain is generally used when
Transition probabilities are fairly stable
Change in transition probabilities is random
No sufficient data are available
All of the above
Which of the following is not one of the assumptions of Markov analysis:
There are a limited number of possible states
A future state can be predicted from the preceding
There are limited number of future periods
All of the above
Markov analysis is useful to answer following questions:
Predicting the state of the system at some future time?
Calculation transition probabilities at some future time?
All of the above
None of the above
The objective of network analysis is to
Minimize total project duration
Minimize total project cost
Minimize production delays, interruption and conflicts
All of the above
Network models have advantage in terms of project
Planning
Scheduling
Controlling
All of the above
Float or slack analysis is useful for
Projects behind the schedule only
Projects ahead of the schedule only
Both 1and 2
None of the above
The activity, which can be delayed without affection the execution of the immediate succeeding activity, is determined by
Total float
Free float
Independent float
None of the above
In time cost-trade-off function analysis
Cost decreases linearly as time increases
Cost at normal time is zero
Cost increases linearly as time increases
None of the above
Of all paths through the network, the critical path
Has the maximum expected time
Has the minimum expected time
Has the maximum actual time
Has the minimum actual time
Estimating expected activity times in a PERT network
Makes use of three estimates
Puts the greatest weight on the most likely time estimate
Is motivated by a beta distribution
All of the above
The calculation of the probability that the critical path will be completed by time T
Assumes that activity times are statistically independent
Assumes that total time of the critical path has approximately a beta distribution
Requires knowledge of the standard deviation for all activities in the network
All of the above
The slack for an activity is equal to
LF – LS
EF – ES
LS – ES
None of the above
In the CPM time-cost trade-off function,
The cost at normal time id 0
Within the range of feasible times, the activity cost increases linearly as increases
Cost decreases linearly as time increases
None of the above
The marginal cost of crashing a network could change when
The activity being crashed reaches its crash time
The activity being crashed reaches a point where another path is also critical
Both 1 and 2
The PERT /Cost model assumes that
Each activity achieves its optimistic time
The costs are uniformly distributed over the life of the activity
That activity times are statistically independent
None of the above
Customer behavior in which he moves from one queue to another in a multiple channel situation is
Balking
Reneging
Jockeying
Alternating
Which of the following characteristics apply to queuing system
Customer population
Arrival process
Both 1 and 2
Neither 1 nor 2
Which of the following is not a key operating characteristics for a queuing system
Utilization factor
Percent idle time
Average time spent waiting spent waiting in the system and queue
None of the above
Priority queue discipline may be classified as
Finite or infinite
Limited and unlimited
Pre-emptive or non-pre-emptive
All of the above
Which symbol describes the inter-arrival time distribution
D
M
G
All of the above
The calling population is assumed to be infinite when
Arrivals are independent of each other
Capacity of the system is infinite
Service rate is faster than arrival rate
All of the above
Which of the cost estimates and performance measures are not used for economic analysis of a queuing system
Cost per server per unit of time
Cost per unit of time for a customer waiting in the system
Average number of customers in the system
Average waiting time of customers in the system
A calling population is considered to be infinite when
All customers arrive at once
Arrivals are independent of each other
Arrivals are dependent upon each other
All of the above
The cost of providing service in a queuing system decreases with
Decreased average waiting time in the queue
Decreased arrival rate
Increased arrival rate
None of the above
A queue is formed when
Customers wait for services
Service facilities stand idle and wait for customers
Either 1 or 2
Both
None
Once a queue model has been constructed, analysis of the model can be performed in
Through analytical solution
Through simulation
Either 1 or 2
Both
None
A model has the following characteristics
Input process or Arrival Pattern
Service Mechanism or Service Pattern
Queue Discipline
Customer’s Behavior
Maximum number of customers allowed in a system
Calling source of population
Which of the following does not apply to the basic queuing model?
Exponentially distributed arrivals
Exponentially distributed service times
Finite time horizon
Unlimited queue size
The discipline is first-come first served
A major goal of queuing is to
Minimize the cost of providing service
Provide models which help the manager to trade off the cost of service
Maximize expected return
Optimize system characteristics
Characteristics of queues such as “expected number in the system”
Are relevant after the queue has reached a steady state
Are probabilistic statements
Depend on the specific model
All of the above
The most difficult aspect of performing a formal economic analysis of queuing
Estimating the service cost
Estimating the waiting cost
Estimating use
The role of artificial variables in the simplex method is
To aid in finding an initial solution
To find optimal dual prices in the final simplex table
To start phase 1 of simplex method
All of the above
For a maximization problem, the objective function coefficient for an artificial variable is
+ M
- M
Zero
None of the above
If a negative value appears in the solution values (XB) column of the simplex table, then
The solution s optimal
The solution is infeasible
The solution is unbounded
All of the above
At every iteration of simplex method, for minimization problem, a variable in the current basis is replaced with another variable that has_______
A positive Cj – Zj value
A negative Cj – Zj value
None of the above
In the optimal simplex table, Cj – Zj = 0 value indicates
Unbounded solution
Cycling
Alternative solution
Infeasible solution
For a maximization LP model, the simplex method is terminated when all values______
Cj – Zj = 0
Cj – Zj = 0
A variable which does not appear in the basic variable (B) column of simplex table is
Never equal to zero
Always equal to zero
Called a basic variable
None of the above
If for a given solution, a slack variable is equal to zero, then
The solution is optimal
The solution is infeasible
The entire amount of resource in which the slack variable appears has been consumed
All of the above
If an optimal solution is degenerate, then
There are alternative optimal solutions
The solution is infeasible
The solution is of no use to the decision-maker
None of the above
To formulate a problem for solution by the simplex method, we must add artificial variable to
Only equality constraints
One ‘greater than’ constraints
Both 1 and 2
None of the above
When making a pivot in the simplex method, the inter-sectional elements are always found in the
Cj – Zj row
Optimal column
Quantity column
None of the above
Suppose that one of the substitution rates in a simplex tableau is negative. This implies that:
Adding one unit of the variable heading that column to the production mix would result in a possible increase in the number of units in the production mix for the quantity corresponding to that row
Adding one unit of the variable heading tat column to the production mix would decrease the quantity of the row variable in the production mix
The variable corresponding to that row will not leave the solution on this iteration
Both 1 and 3
Every tableau in the simplex method
Exhibits a solution to the original equations
Exhibits a basic feasible solution to the equations in the standard equality form of the model
Corresponds to an extreme point of the constraint set
Exhibits a set of transformed equations
All of the above
Which of the following is not true of the simplex method?
At each iteration, the objective value either stays the same or improve
It indicates an unbounded or infeasible problem
It signals optimality
It coverges in at most m steps, where m is the number of constraint
Infeasibility is discovered
In computing the entering variable
In computing the departing variable
None of the above
Suppose that in a non-degenerate optimal tableau, a slack variable S2 is b second constraint, whose RHS is b2. this means that
The original problem is infeasible
All of b2 is used up in the optimal solution
Both the dual price and the optimal value of the dual variable, for constraint, are zero
A better OV could be obtained by increasing b2
The simplex method has the property that:
At each iteration it gives a solution which is at least as good as solution
At each stage it produces feasible solution
It signals that optimal solution has been found
None of the above