Let ‘ai ‘ denote the availability and ‘bj ‘ denote the requirement. Then,
Σai = 30 + 50 + 20 = 100 and Σbj = 30 + 40 + 20 + 10 = 100
Since Σai = Σbj . the given problem is a balanced transportation problem and we can get an initial basic feasible solution.
(a) Least Cost Method (LCM) :
First allocation:
Second allocation:
Third allocation:
Fourth allocation:
Fifth allocation:
We first allocate 10 units to cell (O2 , D2 ). Since it has a minimum cost. Then we allocate the balance 10 units to cell (O1 , D2 ). Thus we get the final allocation table as given below.
Transportation schedule:
O1 → D2 , O1 → D3 , O2 → D1 , O2 → D2 , O2 → D4 , O3 → D2
(i.e) x12 = 10, x13 = 20, x21 = 30, x22 = 10, x24 = 10, x32 = 20
The total cost is = (10 × 8) + (20 × 3) + (30 × 4) + (10 × 5) + (10 × 4) + (20 × 2)
= 80 + 60+ 120 + 50 + 40 + 40
= 390
Thus the LCM, we get the minimum cost for the transportation problem as Rs. 390.
(b) Vogel’s approximation method:
First allocation:
The largest penalty = 3. So allocate 20 units to the cell (O3 , D2 ) which has the least cost in column D2
Second allocation:
Largest penalty = 4. So allocate min (20, 30) units to the cell (O1 , D3 ) which has the least cost in column D3
Third allocation:
The largest penalty is 3. So allocate min (20, 50) to the cell (O2 , D2 ) which has the least cost in column D2 .
Fourth allocation:
Largest penalty = 2. So allocate min (10, 30) to cell (O2 , D4 ) which has the least cost in column D4
Fifth allocation:
Largest penalty = 1. Allocate min (30, 20) to cell (O2 , D1 ) which has the least cost in column D1 . Finally allot the balance 10 units to cell (O1 , D1 )
We get the final allocation table as follows.
Transportation schedule:
O1 → D1 , O1 → D3 , O2 → D1 , O2 → D2 , O2 → D4 , O3 → D2
(i.e) x11 = 10, x13 = 20, x21 = 20, x22 = 20, x24 = 10, x32
= 20
Total cost is given by = (10 × 5) + (20 × 3) + (20 × 4) + (20 × 5) + (10 × 4) + (20 × 2)
= 50 + 60 + 80+ 100 + 40 + 40
= 370
Hence the minimum cost by YAM is Rs. 370