1. Find Solution using Voggel's Approximation method, also find optimal solution using modi method,
| D1 | D2 | D3 | D4 | Supply |
S1 | 19 | 30 | 50 | 10 | 7 |
S2 | 70 | 30 | 40 | 60 | 9 |
S3 | 40 | 8 | 70 | 20 | 18 |
Demand | 5 | 8 | 7 | 14 | |
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` | 19 | 30 | 50 | 10 | | 7 |
`S_2` | 70 | 30 | 40 | 60 | | 9 |
`S_3` | 40 | 8 | 70 | 20 | | 18 |
|
Demand | 5 | 8 | 7 | 14 | | |
Table-1
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19 | 30 | 50 | 10 | | 7 | `9=19-10` |
`S_2` | 70 | 30 | 40 | 60 | | 9 | `10=40-30` |
`S_3` | 40 | 8 | 70 | 20 | | 18 | `12=20-8` |
|
Demand | 5 | 8 | 7 | 14 | | | |
Column Penalty | `21=40-19` | `22=30-8` | `10=50-40` | `10=20-10` | | | |
The maximum penalty, 22, occurs in column `D_2`.
The minimum `c_(ij)` in this column is `c_32` = 8.
The maximum allocation in this cell is min(18,8) =
8.
It satisfy demand of `D_2` and adjust the supply of `S_3` from 18 to 10 (18 - 8 = 10).
Table-2
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19 | 30 | 50 | 10 | | 7 | `9=19-10` |
`S_2` | 70 | 30 | 40 | 60 | | 9 | `20=60-40` |
`S_3` | 40 | 8(8) | 70 | 20 | | 10 | `20=40-20` |
|
Demand | 5 | 0 | 7 | 14 | | | |
Column Penalty | `21=40-19` | -- | `10=50-40` | `10=20-10` | | | |
The maximum penalty, 21, occurs in column `D_1`.
The minimum `c_(ij)` in this column is `c_11` = 19.
The maximum allocation in this cell is min(7,5) =
5.
It satisfy demand of `D_1` and adjust the supply of `S_1` from 7 to 2 (7 - 5 = 2).
Table-3
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19(5) | 30 | 50 | 10 | | 2 | `40=50-10` |
`S_2` | 70 | 30 | 40 | 60 | | 9 | `20=60-40` |
`S_3` | 40 | 8(8) | 70 | 20 | | 10 | `50=70-20` |
|
Demand | 0 | 0 | 7 | 14 | | | |
Column Penalty | -- | -- | `10=50-40` | `10=20-10` | | | |
The maximum penalty, 50, occurs in row `S_3`.
The minimum `c_(ij)` in this row is `c_34` = 20.
The maximum allocation in this cell is min(10,14) =
10.
It satisfy supply of `S_3` and adjust the demand of `D_4` from 14 to 4 (14 - 10 = 4).
Table-4
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19(5) | 30 | 50 | 10 | | 2 | `40=50-10` |
`S_2` | 70 | 30 | 40 | 60 | | 9 | `20=60-40` |
`S_3` | 40 | 8(8) | 70 | 20(10) | | 0 | -- |
|
Demand | 0 | 0 | 7 | 4 | | | |
Column Penalty | -- | -- | `10=50-40` | `50=60-10` | | | |
The maximum penalty, 50, occurs in column `D_4`.
The minimum `c_(ij)` in this column is `c_14` = 10.
The maximum allocation in this cell is min(2,4) =
2.
It satisfy supply of `S_1` and adjust the demand of `D_4` from 4 to 2 (4 - 2 = 2).
Table-5
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19(5) | 30 | 50 | 10(2) | | 0 | -- |
`S_2` | 70 | 30 | 40 | 60 | | 9 | `20=60-40` |
`S_3` | 40 | 8(8) | 70 | 20(10) | | 0 | -- |
|
Demand | 0 | 0 | 7 | 2 | | | |
Column Penalty | -- | -- | `40` | `60` | | | |
The maximum penalty, 60, occurs in column `D_4`.
The minimum `c_(ij)` in this column is `c_24` = 60.
The maximum allocation in this cell is min(9,2) =
2.
It satisfy demand of `D_4` and adjust the supply of `S_2` from 9 to 7 (9 - 2 = 7).
Table-6
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19(5) | 30 | 50 | 10(2) | | 0 | -- |
`S_2` | 70 | 30 | 40 | 60(2) | | 7 | `40` |
`S_3` | 40 | 8(8) | 70 | 20(10) | | 0 | -- |
|
Demand | 0 | 0 | 7 | 0 | | | |
Column Penalty | -- | -- | `40` | -- | | | |
The maximum penalty, 40, occurs in row `S_2`.
The minimum `c_(ij)` in this row is `c_23` = 40.
The maximum allocation in this cell is min(7,7) =
7.
It satisfy supply of `S_2` and demand of `D_3`.
Initial feasible solution is
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | Row Penalty |
`S_1` | 19(5) | 30 | 50 | 10(2) | | 7 | 9 | 9 | 40 | 40 | -- | -- | |
`S_2` | 70 | 30 | 40(7) | 60(2) | | 9 | 10 | 20 | 20 | 20 | 20 | 40 | |
`S_3` | 40 | 8(8) | 70 | 20(10) | | 18 | 12 | 20 | 50 | -- | -- | -- | |
|
Demand | 5 | 8 | 7 | 14 | | | |
Column Penalty | 21 21 -- -- -- --
| 22 -- -- -- -- --
| 10 10 10 10 40 40
| 10 10 10 50 60 --
| | | |
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
Optimality test using modi method...
Allocation Table 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 |
|
Demand | 5 | 8 | 7 | 14 | | |
Iteration-1 of optimality test
1. Find `u_i` and `v_j` for all occupied cells(i,j), where `c_(ij) = u_i + v_j`
`1.` Substituting, `v_4 = 0`, we get
`2. c_14 = u_1 + v_4=>u_1 = c_14 - v_4=>u_1 = 10 -0=>u_1 = 10`
`3. c_11 = u_1 + v_1=>v_1 = c_11 - u_1=>v_1 = 19 -10=>v_1 = 9`
`4. c_24 = u_2 + v_4=>u_2 = c_24 - v_4=>u_2 = 60 -0=>u_2 = 60`
`5. c_23 = u_2 + v_3=>v_3 = c_23 - u_2=>v_3 = 40 -60=>v_3 = -20`
`6. c_34 = u_3 + v_4=>u_3 = c_34 - v_4=>u_3 = 20 -0=>u_3 = 20`
`7. c_32 = u_3 + v_2=>v_2 = c_32 - u_3=>v_2 = 8 -20=>v_2 = -12`
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | `u_i` |
`S_1` | 19 (5) | 30 | 50 | 10 (2) | | 7 | `u_1=10` |
`S_2` | 70 | 30 | 40 (7) | 60 (2) | | 9 | `u_2=60` |
`S_3` | 40 | 8 (8) | 70 | 20 (10) | | 18 | `u_3=20` |
|
Demand | 5 | 8 | 7 | 14 | | | |
`v_j` | `v_1=9` | `v_2=-12` | `v_3=-20` | `v_4=0` | | | |
2. Find `d_(ij)` for all unoccupied cells(i,j), where `d_(ij) = c_(ij) - (u_i + v_j)``1. d_12 = c_12 - (u_1 + v_2) = 30 - (10 -12) = color{blue}{32} `
`2. d_13 = c_13 - (u_1 + v_3) = 50 - (10 -20) = color{blue}{60} `
`3. d_21 = c_21 - (u_2 + v_1) = 70 - (60 +9) = color{blue}{1} `
`4. d_22 = c_22 - (u_2 + v_2) = 30 - (60 -12) = color{blue}{-18} `
`5. d_31 = c_31 - (u_3 + v_1) = 40 - (20 +9) = color{blue}{11} `
`6. d_33 = c_33 - (u_3 + v_3) = 70 - (20 -20) = color{blue}{70} `
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | `u_i` |
`S_1` | 19 (5) | 30 [32] | 50 [60] | 10 (2) | | 7 | `u_1=10` |
`S_2` | 70 [1] | 30 [-18] | 40 (7) | 60 (2) | | 9 | `u_2=60` |
`S_3` | 40 [11] | 8 (8) | 70 [70] | 20 (10) | | 18 | `u_3=20` |
|
Demand | 5 | 8 | 7 | 14 | | | |
`v_j` | `v_1=9` | `v_2=-12` | `v_3=-20` | `v_4=0` | | | |
3. Now choose the minimum negative value from all `d_(ij)` (opportunity cost) = `d_(22` =
[-18] and draw a closed path from `S_2D_2`.
Closed path is `S_2D_2->S_2D_4->S_3D_4->S_3D_2`
Closed path and plus/minus sign allocation...
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | `u_i` |
`S_1` | 19 (5) | 30 [32] | 50 [60] | 10 (2) | | 7 | `u_1=10` |
`S_2` | 70 [1] | 30 [-18] (+) | 40 (7) | 60 (2) (-) | | 9 | `u_2=60` |
`S_3` | 40 [11] | 8 (8) (-) | 70 [70] | 20 (10) (+) | | 18 | `u_3=20` |
|
Demand | 5 | 8 | 7 | 14 | | | |
`v_j` | `v_1=9` | `v_2=-12` | `v_3=-20` | `v_4=0` | | | |
4. Minimum allocated value among all negative position
(-) on closed path = 2
Substract 2 from all
(-) and Add it to all
(+) | `D_1` | `D_2` | `D_3` | `D_4` | | Supply |
`S_1` | 19 (5) | 30 | 50 | 10 (2) | | 7 |
`S_2` | 70 | 30 (2) | 40 (7) | 60 | | 9 |
`S_3` | 40 | 8 (6) | 70 | 20 (12) | | 18 |
|
Demand | 5 | 8 | 7 | 14 | | |
5. Repeat the step 1 to 4, until an optimal solution is obtained.
Iteration-2 of optimality test
1. Find `u_i` and `v_j` for all occupied cells(i,j), where `c_(ij) = u_i + v_j`
`1.` Substituting, `u_1 = 0`, we get
`2. c_11 = u_1 + v_1=>v_1 = c_11 - u_1=>v_1 = 19 -0=>v_1 = 19`
`3. c_14 = u_1 + v_4=>v_4 = c_14 - u_1=>v_4 = 10 -0=>v_4 = 10`
`4. c_34 = u_3 + v_4=>u_3 = c_34 - v_4=>u_3 = 20 -10=>u_3 = 10`
`5. c_32 = u_3 + v_2=>v_2 = c_32 - u_3=>v_2 = 8 -10=>v_2 = -2`
`6. c_22 = u_2 + v_2=>u_2 = c_22 - v_2=>u_2 = 30 +2=>u_2 = 32`
`7. c_23 = u_2 + v_3=>v_3 = c_23 - u_2=>v_3 = 40 -32=>v_3 = 8`
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | `u_i` |
`S_1` | 19 (5) | 30 | 50 | 10 (2) | | 7 | `u_1=0` |
`S_2` | 70 | 30 (2) | 40 (7) | 60 | | 9 | `u_2=32` |
`S_3` | 40 | 8 (6) | 70 | 20 (12) | | 18 | `u_3=10` |
|
Demand | 5 | 8 | 7 | 14 | | | |
`v_j` | `v_1=19` | `v_2=-2` | `v_3=8` | `v_4=10` | | | |
2. Find `d_(ij)` for all unoccupied cells(i,j), where `d_(ij) = c_(ij) - (u_i + v_j)``1. d_12 = c_12 - (u_1 + v_2) = 30 - (0 -2) = color{blue}{32} `
`2. d_13 = c_13 - (u_1 + v_3) = 50 - (0 +8) = color{blue}{42} `
`3. d_21 = c_21 - (u_2 + v_1) = 70 - (32 +19) = color{blue}{19} `
`4. d_24 = c_24 - (u_2 + v_4) = 60 - (32 +10) = color{blue}{18} `
`5. d_31 = c_31 - (u_3 + v_1) = 40 - (10 +19) = color{blue}{11} `
`6. d_33 = c_33 - (u_3 + v_3) = 70 - (10 +8) = color{blue}{52} `
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply | `u_i` |
`S_1` | 19 (5) | 30 [32] | 50 [42] | 10 (2) | | 7 | `u_1=0` |
`S_2` | 70 [19] | 30 (2) | 40 (7) | 60 [18] | | 9 | `u_2=32` |
`S_3` | 40 [11] | 8 (6) | 70 [52] | 20 (12) | | 18 | `u_3=10` |
|
Demand | 5 | 8 | 7 | 14 | | | |
`v_j` | `v_1=19` | `v_2=-2` | `v_3=8` | `v_4=10` | | | |
Since all `d_(ij)>=0`.
So final optimal solution is arrived.
| `D_1` | `D_2` | `D_3` | `D_4` | | Supply |
`S_1` | 19 (5) | 30 | 50 | 10 (2) | | 7 |
`S_2` | 70 | 30 (2) | 40 (7) | 60 | | 9 |
`S_3` | 40 | 8 (6) | 70 | 20 (12) | | 18 |
|
Demand | 5 | 8 | 7 | 14 | | |
The minimum total transportation cost `= 19 xx 5 + 10 xx 2 + 30 xx 2 + 40 xx 7 + 8 xx 6 + 20 xx 12 = 743`