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5. column minima method example ( Enter your problem )
Algorithm and examples
  1. Algorithm & Example-1
  2. Example-2
  3. Unbalanced supply and demand 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)

4. Row minima method
(Previous method)
2. Example-2
(Next example)

1. Algorithm & Example-1





Algorithm
Column minima method Steps (Rule)
Step-1: In this method, we allocate as much as possible in the lowest cost cell of the first Column, i.e. allocate `min(s_i, d_j)`.
Step-2: a. Subtract this `min` value from supply `s_i` and demand `d_j`.

b. If the supply `s_i` is 0, then cross (strike) that row and If the demand `d_j` is 0 then cross (strike) that column.

c. If min unit cost cell is not unique, then select the cell where maximum allocation can be possible
Step-3: Repeat this process for all uncrossed (unstriked) rows and columns until all supply and demand values are 0.

Example-1
Find Solution using Column minima method
D1D2D3D4Supply
S1193050107
S2703040609
S3408702018
Demand58714


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`193050107
`S_2`703040609
`S_3`408702018
Demand58714


In `1^(st)` column, The smallest transportation cost is 19 in cell `S_1 D_1`

The allocation to this cell is min(7,5) = 5.
This satisfies the entire demand of `D_1` and leaves 7 - 5 = 2 units with `S_1`

Table-1
`D_1``D_2``D_3``D_4`Supply
`S_1`19(5)3050102
`S_2`703040609
`S_3`408702018
Demand08714


In `2^(nd)` column, The smallest transportation cost is 8 in cell `S_3 D_2`

The allocation to this cell is min(18,8) = 8.
This satisfies the entire demand of `D_2` and leaves 18 - 8 = 10 units with `S_3`

Table-2
`D_1``D_2``D_3``D_4`Supply
`S_1`19(5)3050102
`S_2`703040609
`S_3`408(8)702010
Demand00714


In `3^(rd)` column, The smallest transportation cost is 40 in cell `S_2 D_3`

The allocation to this cell is min(9,7) = 7.
This satisfies the entire demand of `D_3` and leaves 9 - 7 = 2 units with `S_2`

Table-3
`D_1``D_2``D_3``D_4`Supply
`S_1`19(5)3050102
`S_2`703040(7)602
`S_3`408(8)702010
Demand00014


In `4^(th)` column, The smallest transportation cost is 10 in cell `S_1 D_4`

The allocation to this cell is min(2,14) = 2.
This exhausts the capacity of `S_1` and leaves 14 - 2 = 12 units with `D_4`

Table-4
`D_1``D_2``D_3``D_4`Supply
`S_1`19(5)305010(2)0
`S_2`703040(7)602
`S_3`408(8)702010
Demand00012


In `4^(th)` column, The smallest transportation cost is 20 in cell `S_3 D_4`

The allocation to this cell is min(10,12) = 10.
This exhausts the capacity of `S_3` and leaves 12 - 10 = 2 units with `D_4`

Table-5
`D_1``D_2``D_3``D_4`Supply
`S_1`19(5)305010(2)0
`S_2`703040(7)602
`S_3`408(8)7020(10)0
Demand0002


In `4^(th)` column, The smallest transportation cost is 60 in cell `S_2 D_4`

The allocation to this cell is min(2,2) = 2.
Table-6
`D_1``D_2``D_3``D_4`Supply
`S_1`19(5)305010(2)0
`S_2`703040(7)60(2)0
`S_3`408(8)7020(10)0
Demand0000


Initial feasible solution is
`D_1``D_2``D_3``D_4`Supply
`S_1`19 (5)30 50 10 (2)7
`S_2`70 30 40 (7)60 (2)9
`S_3`40 8 (8)70 20 (10)18
Demand58714


The minimum total transportation cost `= 19 xx 5 + 10 xx 2 + 40 xx 7 + 60 xx 2 + 8 xx 8 + 20 xx 10 = 779`

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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4. Row minima method
(Previous method)
2. Example-2
(Next example)





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