Question:

An oil company has two depots A and B with capacities of 7000 L and 4000 L respectively.The company is to supply oil to three petrol pumps D, E and F whose requirements are 4500 L, 3000 L and 3500 L respectively. The distance (in km) between the depots and the petrol pumps is given in the following table: 

Distance (in km)
From/ToAB
D73
E64
F32

Assuming that the transportation cost of 10litres of oil is Re1 per km,how should the delivery be scheduled in order that the transportation cost is minimum? What is the minimum cost?

Updated On: Sep 21, 2023
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Solution and Explanation

Let x and y litres of oil be supplied from A to the petrol pumps, D and E.

Then, ( 7000 - x - y ) will be supplied tA to petrol pump F.

The requirement of petrol pump D is 4500 L.

Since xL are transported from depot A, the remaining (4500-x) L will be the transported from petrol pump B. Similarly, (3000-y) L and 3500-(7000-x-y) = (x+y-3500) L will be transported from depot B to petrol pump E and F respectively.

The given problem can be represented diagrammatically as follows. 

The given problem can be represented diagrammatically

x≥0,y≥0, and (700-x-y)≥0  

⇒ x≥0,y≥0, and x+y≤7000 

4500-x≥0,3000-y≥0, and x+y-3500≥0  

⇒ x≤4500, y≤3000, and x+y≥3500

Cost of transporting 10L of petrol = Re 1

Cost of transporting 1L of petrol = Rs \(\frac {1}{10}\)

Therefore, total transportation cost is given by, 

\(Z =\frac {7}{10}  \times x+  \frac {6}{10}×y+\frac {3}{10}(7000-x-y)+\frac {3}{10}(4500-x)+\frac {4}{10}(3000-y)+\frac {2}{10}(x+y-3500)\)

\(Z = 0.3x+0.1y+3950\)

The problem can be formulated as follows.

Minimize Z = 0.3x+0.1y+3950               ....(1)

Subject to the constraints,
x+y≤7000          .....(2)
x≤4500              ......(3)
y≤3000              ......(4)
x+y≥3500          ......(5)
x,y≥0                  ......(6)

The feasible region determined by the constraints is as follows.

The feasible region determined by the constraints

The corner points of the feasible region are A(3500, 0), B(4500, 0), C(4500, 2500), D(4000, 3000),and E(500, 3000).

The values of Z at these corner points are as follows.

Corner pointz = 0.3x + 0.1y + 3950 
A (3500, 0)5000 
B (4500, 0)5300 
C (4500, 2500)5550 
(4000, 3000)5450 
(500, 3000)4400\(\to\) Minimum

The minimum value of Z is 4400 at (500, 3000).

Thus, the oil supplied from depot A is 500 L, 3000 L and 3500 L and from depot B is 4000 L, 0 L and 0 L to petrol pumps D, E and F respectively. The minimum transportation cost is Rs 4400.

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Concepts Used:

Linear Programming Problems

The Linear Programming Problems (LPP) is a problem that is concerned with finding the optimal value of the given linear function. The optimal value can be either maximum value or minimum value. Here, the given linear function is considered an objective function. The objective function can contain several variables, which are subjected to the conditions and it has to satisfy the set of linear inequalities called linear constraints.

Linear Programming Simplex Method

Step 1: Establish a given problem. (i.e.,) write the inequality constraints and objective function.

Step 2: Convert the given inequalities to equations by adding the slack variable to each inequality expression.

Step 3: Create the initial simplex tableau. Write the objective function at the bottom row. Here, each inequality constraint appears in its own row. Now, we can represent the problem in the form of an augmented matrix, which is called the initial simplex tableau.

Step 4: Identify the greatest negative entry in the bottom row, which helps to identify the pivot column. The greatest negative entry in the bottom row defines the largest coefficient in the objective function, which will help us to increase the value of the objective function as fastest as possible.

Step 5: Compute the quotients. To calculate the quotient, we need to divide the entries in the far right column by the entries in the first column, excluding the bottom row. The smallest quotient identifies the row. The row identified in this step and the element identified in the step will be taken as the pivot element.

Step 6: Carry out pivoting to make all other entries in column is zero.

Step 7: If there are no negative entries in the bottom row, end the process. Otherwise, start from step 4.

Step 8: Finally, determine the solution associated with the final simplex tableau.