Infeasible solution
If there is no any solution that satifies all the constraints, then it is called Infeasible solution
In the final simplex table when all `c_j - z_j` imply optimal solution but at least one artificial variable present in the basis with positive value. Then the problem has no feasible solution.
Example
Find solution using Two-Phase method
MIN Z = X1 - 2X2 - 3X3
subject to
-2X1 + X2 + 3X3 = 2
2X1 + 3X2 + 4X3 = 1
and X1,X2,X3 >= 0; Solution:Problem is | Min `Z` | `=` | `` | `` | `X_1` | ` - ` | `2` | `X_2` | ` - ` | `3` | `X_3` |
|
| subject to |
| ` - ` | `2` | `X_1` | ` + ` | `` | `X_2` | ` + ` | `3` | `X_3` | = | `2` | | `` | `2` | `X_1` | ` + ` | `3` | `X_2` | ` + ` | `4` | `X_3` | = | `1` |
|
| and `X_1,X_2,X_3 >= 0; ` |
-->Phase-1<--
The problem is converted to canonical form by adding slack, surplus and artificial variables as appropiate
1. As the constraint-1 is of type '`=`' we should add artificial variable `A_1`
2. As the constraint-2 is of type '`=`' we should add artificial variable `A_2`
After introducing artificial variables| Min `Z` | `=` | | | | | | | | | | `` | `` | `A_1` | ` + ` | `` | `A_2` |
|
| subject to |
| ` - ` | `2` | `X_1` | ` + ` | `` | `X_2` | ` + ` | `3` | `X_3` | ` + ` | `` | `A_1` | | | | = | `2` | | `` | `2` | `X_1` | ` + ` | `3` | `X_2` | ` + ` | `4` | `X_3` | | | | ` + ` | `` | `A_2` | = | `1` |
|
| and `X_1,X_2,X_3,A_1,A_2 >= 0` |
| `Z` | | | | | | | | | | ` - ` | `` | `A_1` | ` - ` | `` | `A_2` | = | `0` |
|
| ` - ` | `2` | `X_1` | ` + ` | `` | `X_2` | ` + ` | `3` | `X_3` | ` + ` | `` | `A_1` | | | | = | `2` | | `` | `2` | `X_1` | ` + ` | `3` | `X_2` | ` + ` | `4` | `X_3` | | | | ` + ` | `` | `A_2` | = | `1` |
|
Simplex tableau is
Tableau-0
| `"Basis"` | `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` | |
| `R_1` `Z` | `0` | `0` | `0` | `-1` | `-1` | `0` | |
| `R_2` `A_1` | `-2` | `1` | `3` | `1` | `0` | `2` | |
| `R_3` `A_2` | `2` | `3` | `4` | `0` | `1` | `1` | |
Make the Z-row consistent with the rest of the table (set coefficient of basis variables to 0 in Z-row)
`R_1`(new)`= R_1`(old) + `R_2`(old)
| `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` |
| `R_1`(old) = | `0` | `0` | `0` | `-1` | `-1` | `0` |
| `R_2`(old) = | `-2` | `1` | `3` | `1` | `0` | `2` |
| `R_1`(new)`= R_1`(old) + `R_2`(old) | `-2` | `1` | `3` | `0` | `-1` | `2` |
`R_1`(new)`= R_1`(old) + `R_3`(old)
| `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` |
| `R_1`(old) = | `-2` | `1` | `3` | `0` | `-1` | `2` |
| `R_3`(old) = | `2` | `3` | `4` | `0` | `1` | `1` |
| `R_1`(new)`= R_1`(old) + `R_3`(old) | `0` | `4` | `7` | `0` | `0` | `3` |
Tableau-1
| `"Basis"` | `X_1` | `X_2` | `X_3``darr` | `A_1` | `A_2` | `RHS` | `"Ratio"=(RHS)/(X_3)` |
| `R_1` `Z` | `0` | `4` | `7` | `0` | `0` | `3` | |
| `R_2` `A_1` | `-2` | `1` | `3` | `1` | `0` | `2` | `(2)/(3)=0.6667` |
| `R_3` `A_2` | `2` | `3` | `(4)` | `0` | `1` | `1` | `(1)/(4)=0.25``->` |
Most Positive `Z` is `7`. So,
the entering variable is `X_3`.
Minimum ratio is `0.25`. So,
the leaving basis variable is `A_2`.
`:.`
The pivot element is `4`.
Entering `=X_3`, Departing `=A_2`, Key Element `=4`
`R_3`(new)`= R_3`(old) `-: 4`
| `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` |
| `R_3`(old) = | `2` | `3` | `4` | `0` | `1` | `1` |
| `R_3`(new)`= R_3`(old) `-: 4` | `0.5` | `0.75` | `1` | `0` | `0.25` | `0.25` |
`R_2`(new)`= R_2`(old) - `3 R_3`(new)
| `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` |
| `R_2`(old) = | `-2` | `1` | `3` | `1` | `0` | `2` |
| `R_3`(new) = | `0.5` | `0.75` | `1` | `0` | `0.25` | `0.25` |
| `3 xx R_3`(new) = | `1.5` | `2.25` | `3` | `0` | `0.75` | `0.75` |
| `R_2`(new)`= R_2`(old) - `3 R_3`(new) | `-3.5` | `-1.25` | `0` | `1` | `-0.75` | `1.25` |
`R_1`(new)`= R_1`(old) - `7 R_3`(new)
| `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` |
| `R_1`(old) = | `0` | `4` | `7` | `0` | `0` | `3` |
| `R_3`(new) = | `0.5` | `0.75` | `1` | `0` | `0.25` | `0.25` |
| `7 xx R_3`(new) = | `3.5` | `5.25` | `7` | `0` | `1.75` | `1.75` |
| `R_1`(new)`= R_1`(old) - `7 R_3`(new) | `-3.5` | `-1.25` | `0` | `0` | `-1.75` | `1.25` |
Tableau-2
| `"Basis"` | `X_1` | `X_2` | `X_3` | `A_1` | `A_2` | `RHS` | |
| `R_1` `Z` | `-3.5` | `-1.25` | `0` | `0` | `-1.75` | `1.25` | |
| `R_2` `A_1` | `-3.5` | `-1.25` | `0` | `1` | `-0.75` | `1.25` | |
| `R_3` `X_3` | `0.5` | `0.75` | `1` | `0` | `0.25` | `0.25` | |
Since all `Z_j <= 0`
Hence, optimal solution is arrived with value of variables as :
`X_1=0,X_2=0,X_3=0.25`
Min `Z=0`
But this solution is not feasible (and also not optimal)because the solution violates the `1^(st)` constraint ` - ` `2` `X_1` ` + ` `` `X_2` ` + ` `3` `X_3` = `2`.
and the artificial variable `A_1` appears in the basis with positive value `1.25`
So phase-2 is not possbile.
This material is intended as a summary. Use your textbook for detail explanation.
Any bug, improvement, feedback then