# At the optimum level (i.e. final iteration) values of the slack variables in the primal are

1.  Positive

2.  Negative

3.  Zero

4.   None of these

4

Zero

Explanation :
No Explanation available for this question

# The performance of a system, as expressed in the form of linear programming model can be improved by

1.  Increasing the activities contribution

2.  Increasing the availability of resources

3.  Reducing the activities consumption of resources

4.   All of these

4

All of these

Explanation :
No Explanation available for this question

# The index row value,(cj – zi) in the simplex table indicates

1.  That the variable in the corresponding column of its maximum value is the one that enters the base in the next iteration

2.  Profit per unit of the product of the concerned decision variable in that column

3.  Increase in the value of the object function in the next iteration, if its corresponding variable in that column, enters into the base

4.  That the variable in the corresponding column of its minimum of its minimum value is the one that leaves the base in the next iteration

4

Increase in the value of the object function in the next iteration, if its corresponding variable in that column, enters into the base

Explanation :
No Explanation available for this question

# Transportation models is expressed as

1.  ‘m’ number of sources of supply, each having different capacities of supply Si(i = 1,2,.........,m)

2.  ‘n’ number of destination centres, each having different demand requirements of Dj(j = 1,2, .....,n)

3.  The cost of transporting unit item from source ‘i’ to destination ‘j’ is c0

4.  The number of items transported from source ‘t’ to destination j is x0

5.   All of these

5

All of these

Explanation :
No Explanation available for this question

# The optimality of a transportation problem is determined by the application of

1.  North West Corner Method

2.  Modi Method

3.  Vegel’s Application method(VAM)

4.  Least Cost Method

4

Modi Method

Explanation :
No Explanation available for this question

# In a transportation problem, there are four supply centres and five demand centres. The total quantity of supply available is greater than the total quantity of supply available is greater than the total demand. The number of allocations, without degeneracy during an iteration is

1.  3

2.  6

3.  9

4.  0

4

9

Explanation :
No Explanation available for this question

# Consider the Linear Programme (LP) Max 4x + 6y Subject to 3x + 2y ≤ 6 2x + 3y ≤ 6 X,y ≥ 0 After introducing slack variables s and t, the initial basic feasible solution is represented by the table below (basic variables are s = 6 and t = 6, and the objective function value is 0).   -4 -6 0 0 0 S 3 2 1 0 0 T 2 3 0 1 6   x Y S T RHS After some simplex iteration, the following table is obtained   0 0 0 2 12 S 5/3 0 1 -1/3 2 Y 2/3 1 0 1/3 2   x y s T RHS From this, one can conclude that

1.  The LP has a unique optimal solution

2.  The LP has an optimal solution that is not unique

3.  The LP is infeasible

4.  The LP is unbounded

4

The LP has an optimal solution that is not unique

Explanation :
No Explanation available for this question

# Consider the following Linear Programming Problem (LPP): Maximize z = 3x1 + 2x2 Subject to x1 ≤ 4 x2 ≤ 6 3x1 + 2x2 ≤ 18 x1 ≥ 0, x2 ≥ 0

1.  The LPP has a unique optimal solution

2.  The LPP is infeasible

3.  The LPP is unbounded

4.  The LPP has multiple optimal solutions

4

The LPP has multiple optimal solutions

Explanation :
No Explanation available for this question

# Fulkerson’s rule is connected with

1.  Numbering of event in PERT/CPM

2.  The simulation model

3.  Queuing theory

4.  None of these

4

Numbering of event in PERT/CPM

Explanation :
No Explanation available for this question

# In a transportation model, there are n variables and m constraints. The condition of degeneracy is that during iteration, the total number of allocated base calls should be

1.  Equal to (m + n – 1)

2.  More than (m + n – 1)

3.  Less than (m + n – 1)

4.  None of these

4