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2. least cost method example ( Enter your problem )
Algorithm and examples
  1. Algorithm & Example-1
  2. Example-2
  3. Unbalanced supply and demand example
  4. Prohibited Routes example
Other related methods
  1. north-west corner method
  2. least cost method
  3. vogel's approximation method
  4. Row minima method
  5. Column minima method
  6. Russell's approximation method
  7. Heuristic method-1
  8. Heuristic method-2
  9. modi method (optimal solution)
  10. stepping stone method (optimal solution)

1. Algorithm & Example-1
(Previous example)
3. Unbalanced supply and demand example
(Next example)

2. Example-2





Find Solution using Least Cost method
D1D2D3D4Supply
S111131714250
S216181410300
S321241310400
Demand200225275250


Solution:
TOTAL number of supply constraints : 3
TOTAL number of demand constraints : 4
Problem Table is
`D_1``D_2``D_3``D_4`Supply
`S_1`11131714250
`S_2`16181410300
`S_3`21241310400
Demand200225275250


The smallest transportation cost is 10 in cell `S_3 D_4`

The allocation to this cell is min(400,250) = 250.
This satisfies the entire demand of `D_4` and leaves 400 - 250 = 150 units with `S_3`

Table-1
`D_1``D_2``D_3``D_4`Supply
`S_1`11131714250
`S_2`16181410300
`S_3`21241310(250)150
Demand2002252750


The smallest transportation cost is 11 in cell `S_1 D_1`

The allocation to this cell is min(250,200) = 200.
This satisfies the entire demand of `D_1` and leaves 250 - 200 = 50 units with `S_1`

Table-2
`D_1``D_2``D_3``D_4`Supply
`S_1`11(200)13171450
`S_2`16181410300
`S_3`21241310(250)150
Demand02252750


The smallest transportation cost is 13 in cell `S_3 D_3`

The allocation to this cell is min(150,275) = 150.
This exhausts the capacity of `S_3` and leaves 275 - 150 = 125 units with `D_3`

Table-3
`D_1``D_2``D_3``D_4`Supply
`S_1`11(200)13171450
`S_2`16181410300
`S_3`212413(150)10(250)0
Demand02251250


The smallest transportation cost is 13 in cell `S_1 D_2`

The allocation to this cell is min(50,225) = 50.
This exhausts the capacity of `S_1` and leaves 225 - 50 = 175 units with `D_2`

Table-4
`D_1``D_2``D_3``D_4`Supply
`S_1`11(200)13(50)17140
`S_2`16181410300
`S_3`212413(150)10(250)0
Demand01751250


The smallest transportation cost is 14 in cell `S_2 D_3`

The allocation to this cell is min(300,125) = 125.
This satisfies the entire demand of `D_3` and leaves 300 - 125 = 175 units with `S_2`

Table-5
`D_1``D_2``D_3``D_4`Supply
`S_1`11(200)13(50)17140
`S_2`161814(125)10175
`S_3`212413(150)10(250)0
Demand017500


The smallest transportation cost is 18 in cell `S_2 D_2`

The allocation to this cell is min(175,175) = 175.
Table-6
`D_1``D_2``D_3``D_4`Supply
`S_1`11(200)13(50)17140
`S_2`1618(175)14(125)100
`S_3`212413(150)10(250)0
Demand0000


Initial feasible solution is
`D_1``D_2``D_3``D_4`Supply
`S_1`11 (200)13 (50)17 14 250
`S_2`16 18 (175)14 (125)10 300
`S_3`21 24 13 (150)10 (250)400
Demand200225275250


The minimum total transportation cost `= 11 xx 200 + 13 xx 50 + 18 xx 175 + 14 xx 125 + 13 xx 150 + 10 xx 250 = 12200`

Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6
`:.` This solution is non-degenerate


This material is intended as a summary. Use your textbook for detail explanation.
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1. Algorithm & Example-1
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3. Unbalanced supply and demand example
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