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9. modi method (optimal solution) example ( Enter your problem )
Algorithm and examples
  1. Algorithm & Example-1
  2. Example-2
  3. Alternate optimal solutions example
  4. Degeneracy at initial solution
  5. Degeneracy at subsequent iterations
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)

3. Alternate optimal solutions example
(Previous example)
5. Degeneracy at subsequent iterations
(Next example)

4. Degeneracy at initial solution





Degeneracy
If the basic feasible solution of a transportation problem with m rows and n columns has less than m + n - 1 allocation, then the problem is called degenerate transportation problem.

It may occur at
1. At the initial solution
2. At subsequent iterations of testing of the optimal solution
Example
Find Solution using Voggel's Approximation method, also find optimal solution using modi method,
D1D2D3D4D5Supply
S1586638
S2477655
S3846649
Demand44548


Solution:
TOTAL number of supply constraints : 3
TOTAL number of demand constraints : 5
Problem Table is
`D_1``D_2``D_3``D_4``D_5`Supply
`S_1`586638
`S_2`477655
`S_3`846649
Demand44548


Here Total Demand = 25 is greater than Total Supply = 22. So We add a dummy supply constraint with 0 unit cost and with allocation 3.
Now, The modified table is
`D_1``D_2``D_3``D_4``D_5`Supply
`S_1`586638
`S_2`477655
`S_3`846649
`S_(dummy)`000003
Demand44548


Table-1
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`586638`2=5-3`
`S_2`477655`1=5-4`
`S_3`846649`0=4-4`
`S_(dummy)`000003`0=0-0`
Demand44548
Column
Penalty
`4=4-0``4=4-0``6=6-0``6=6-0``3=3-0`


The maximum penalty, 6, occurs in column `D_3`.

The minimum `c_(ij)` in this column is `c_43` = 0.

The maximum allocation in this cell is min(3,5) = 3.
It satisfy supply of `S_(dummy)` and adjust the demand of `D_3` from 5 to 2 (5 - 3 = 2).

Table-2
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`586638`2=5-3`
`S_2`477655`1=5-4`
`S_3`846649`0=4-4`
`S_(dummy)`000(3)000--
Demand44248
Column
Penalty
`1=5-4``3=7-4``0=6-6``0=6-6``1=4-3`


The maximum penalty, 3, occurs in column `D_2`.

The minimum `c_(ij)` in this column is `c_32` = 4.

The maximum allocation in this cell is min(9,4) = 4.
It satisfy demand of `D_2` and adjust the supply of `S_3` from 9 to 5 (9 - 4 = 5).

Table-3
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`586638`2=5-3`
`S_2`477655`1=5-4`
`S_3`84(4)6645`2=6-4`
`S_(dummy)`000(3)000--
Demand40248
Column
Penalty
`1=5-4`--`0=6-6``0=6-6``1=4-3`


The maximum penalty, 2, occurs in row `S_1`.

The minimum `c_(ij)` in this row is `c_15` = 3.

The maximum allocation in this cell is min(8,8) = 8.
It satisfy supply of `S_1` and demand of `D_5`.

Table-4
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`58663(8)0--
`S_2`477655`2=6-4`
`S_3`84(4)6645`0=6-6`
`S_(dummy)`000(3)000--
Demand40240
Column
Penalty
`4=8-4`--`1=7-6``0=6-6`--


The maximum penalty, 4, occurs in column `D_1`.

The minimum `c_(ij)` in this column is `c_21` = 4.

The maximum allocation in this cell is min(5,4) = 4.
It satisfy demand of `D_1` and adjust the supply of `S_2` from 5 to 1 (5 - 4 = 1).

Table-5
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`58663(8)0--
`S_2`4(4)77651`1=7-6`
`S_3`84(4)6645`0=6-6`
`S_(dummy)`000(3)000--
Demand00240
Column
Penalty
----`1=7-6``0=6-6`--


The maximum penalty, 1, occurs in column `D_3`.

The minimum `c_(ij)` in this column is `c_33` = 6.

The maximum allocation in this cell is min(5,2) = 2.
It satisfy demand of `D_3` and adjust the supply of `S_3` from 5 to 3 (5 - 2 = 3).

Table-6
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`58663(8)0--
`S_2`4(4)77651`6`
`S_3`84(4)6(2)643`6`
`S_(dummy)`000(3)000--
Demand00040
Column
Penalty
------`0=6-6`--


The maximum penalty, 6, occurs in row `S_3`.

The minimum `c_(ij)` in this row is `c_34` = 6.

The maximum allocation in this cell is min(3,4) = 3.
It satisfy supply of `S_3` and adjust the demand of `D_4` from 4 to 1 (4 - 3 = 1).

Table-7
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`58663(8)0--
`S_2`4(4)77651`6`
`S_3`84(4)6(2)6(3)40--
`S_(dummy)`000(3)000--
Demand00010
Column
Penalty
------`6`--


The maximum penalty, 6, occurs in row `S_2`.

The minimum `c_(ij)` in this row is `c_24` = 6.

The maximum allocation in this cell is min(1,1) = 1.
It satisfy supply of `S_2` and demand of `D_4`.


Initial feasible solution is
`D_1``D_2``D_3``D_4``D_5`SupplyRow Penalty
`S_1`58663(8)8 2 |  2 |  2 | -- | -- | -- | -- |
`S_2`4(4)776(1)55 1 |  1 |  1 |  2 |  1 |  6 |  6 |
`S_3`84(4)6(2)6(3)49 0 |  0 |  2 |  0 |  0 |  6 | -- |
`S_(dummy)`000(3)003 0 | -- | -- | -- | -- | -- | -- |
Demand44548
Column
Penalty
4
1
1
4
--
--
--
4
3
--
--
--
--
--
6
0
0
1
1
--
--
6
0
0
0
0
0
6
3
1
1
--
--
--
--


The minimum total transportation cost `= 3 xx 8 + 4 xx 4 + 6 xx 1 + 4 xx 4 + 6 xx 2 + 6 xx 3 + 0 xx 3 = 92`

Here, the number of allocated cells = 7, which is one less than to m + n - 1 = 4 + 5 - 1 = 8
`:.` This solution is degenerate

To resolve degeneracy, we make use of an artifical quantity(d).
The quantity d is assigned to that unoccupied cell, which has the minimum transportation cost.

The quantity d is assigned to `S_3D_5`, which has the minimum transportation cost = 4.

`D_1``D_2``D_3``D_4``D_5`Supply
`S_1`5 8 6 6 3 (8)8
`S_2`4 (4)7 7 6 (1)5 5
`S_3`8 4 (4)6 (2)6 (3)4 (d)9
`S_(dummy)`0 0 0 (3)0 0 3
Demand44548




Optimality test using modi method...
Allocation Table is
`D_1``D_2``D_3``D_4``D_5`Supply
`S_1`5 8 6 6 3 (8)8
`S_2`4 (4)7 7 6 (1)5 5
`S_3`8 4 (4)6 (2)6 (3)4 (d)9
`S_(dummy)`0 0 0 (3)0 0 3
Demand44548


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, `u_3 = 0`, we get

`2. c_32 = u_3 + v_2=>v_2 = c_32 - u_3=>v_2 = 4 -0=>v_2 = 4`

`3. c_33 = u_3 + v_3=>v_3 = c_33 - u_3=>v_3 = 6 -0=>v_3 = 6`

`4. c_43 = u_4 + v_3=>u_4 = c_43 - v_3=>u_4 = 0 -6=>u_4 = -6`

`5. c_34 = u_3 + v_4=>v_4 = c_34 - u_3=>v_4 = 6 -0=>v_4 = 6`

`6. c_24 = u_2 + v_4=>u_2 = c_24 - v_4=>u_2 = 6 -6=>u_2 = 0`

`7. c_21 = u_2 + v_1=>v_1 = c_21 - u_2=>v_1 = 4 -0=>v_1 = 4`

`8. c_35 = u_3 + v_5=>v_5 = c_35 - u_3=>v_5 = 4 -0=>v_5 = 4`

`9. c_15 = u_1 + v_5=>u_1 = c_15 - v_5=>u_1 = 3 -4=>u_1 = -1`

`D_1``D_2``D_3``D_4``D_5`Supply`u_i`
`S_1`5 8 6 6 3 (8)8`u_1=-1`
`S_2`4 (4)7 7 6 (1)5 5`u_2=0`
`S_3`8 4 (4)6 (2)6 (3)4 (d)9`u_3=0`
`S_(dummy)`0 0 0 (3)0 0 3`u_4=-6`
Demand44548
`v_j``v_1=4``v_2=4``v_3=6``v_4=6``v_5=4`


2. Find `d_(ij)` for all unoccupied cells(i,j), where `d_(ij) = c_(ij) - (u_i + v_j)`

`1. d_11 = c_11 - (u_1 + v_1) = 5 - (-1 +4) = color{blue}{2} `

`2. d_12 = c_12 - (u_1 + v_2) = 8 - (-1 +4) = color{blue}{5} `

`3. d_13 = c_13 - (u_1 + v_3) = 6 - (-1 +6) = color{blue}{1} `

`4. d_14 = c_14 - (u_1 + v_4) = 6 - (-1 +6) = color{blue}{1} `

`5. d_22 = c_22 - (u_2 + v_2) = 7 - (0 +4) = color{blue}{3} `

`6. d_23 = c_23 - (u_2 + v_3) = 7 - (0 +6) = color{blue}{1} `

`7. d_25 = c_25 - (u_2 + v_5) = 5 - (0 +4) = color{blue}{1} `

`8. d_31 = c_31 - (u_3 + v_1) = 8 - (0 +4) = color{blue}{4} `

`9. d_41 = c_41 - (u_4 + v_1) = 0 - (-6 +4) = color{blue}{2} `

`10. d_42 = c_42 - (u_4 + v_2) = 0 - (-6 +4) = color{blue}{2} `

`11. d_44 = c_44 - (u_4 + v_4) = 0 - (-6 +6) = color{blue}{0} `

`12. d_45 = c_45 - (u_4 + v_5) = 0 - (-6 +4) = color{blue}{2} `

`D_1``D_2``D_3``D_4``D_5`Supply`u_i`
`S_1`5 [2]8 [5]6 [1]6 [1]3 (8)8`u_1=-1`
`S_2`4 (4)7 [3]7 [1]6 (1)5 [1]5`u_2=0`
`S_3`8 [4]4 (4)6 (2)6 (3)4 (d)9`u_3=0`
`S_(dummy)`0 [2]0 [2]0 (3)0 [0]0 [2]3`u_4=-6`
Demand44548
`v_j``v_1=4``v_2=4``v_3=6``v_4=6``v_5=4`


Since all `d_(ij)>=0`.

So final optimal solution is arrived.
`D_1``D_2``D_3``D_4``D_5`Supply
`S_1`5 8 6 6 3 (8)8
`S_2`4 (4)7 7 6 (1)5 5
`S_3`8 4 (4)6 (2)6 (3)4 (d)9
`S_(dummy)`0 0 0 (3)0 0 3
Demand44548


The minimum total transportation cost `= 3 xx 8 + 4 xx 4 + 6 xx 1 + 4 xx 4 + 6 xx 2 + 6 xx 3 + 0 xx 3 = 92`

Notice alternate solution is available with unoccupied cell `S_(dummy)D_4 : d_(44` = [0], but with the same optimal value.


This material is intended as a summary. Use your textbook for detail explanation.
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3. Alternate optimal solutions example
(Previous example)
5. Degeneracy at subsequent iterations
(Next example)





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