Algorithm
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Two-Phase Method Steps (Rule)
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Step-1:
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Phase-1
a. Form a new objective function by assigning zero to every original variable (including slack and surplus variables) and -1 to each of the artificial variables.
eg. Max Z = - A1 - A2
b. Using simplex method, try to eliminate the artificial varibles from the basis.
c. The solution at the end of Phase-1 is the initial basic feasible solution for Phase-2.
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Step-2:
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Phase-2
a. The original objective function is used and coefficient of artificial variable is 0 (so artificial variable is removed from the calculation process).
b. Then simplex algorithm is used to find optimal solution.
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Example
Find solution using Two-Phase method
MIN Z = x1 + x2
subject to
2x1 + x2 >= 4
x1 + 7x2 >= 7
and x1,x2 >= 0; Solution:Problem is | Min `Z` | `=` | `` | `` | `x_1` | ` + ` | `` | `x_2` |
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| subject to |
| `` | `2` | `x_1` | ` + ` | `` | `x_2` | ≥ | `4` | | `` | `` | `x_1` | ` + ` | `7` | `x_2` | ≥ | `7` |
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| and `x_1,x_2 >= 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 subtract surplus variable `S_1` and add artificial variable `A_1`
2. As the constraint-2 is of type '`>=`' we should subtract surplus variable `S_2` and add artificial variable `A_2`
After introducing surplus,artificial variables| Min `Z` | `=` | | | | | | | | | | | | | `` | `` | `A_1` | ` + ` | `` | `A_2` |
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| subject to |
| `` | `2` | `x_1` | ` + ` | `` | `x_2` | ` - ` | `` | `S_1` | | | | ` + ` | `` | `A_1` | | | | = | `4` | | `` | `` | `x_1` | ` + ` | `7` | `x_2` | | | | ` - ` | `` | `S_2` | | | | ` + ` | `` | `A_2` | = | `7` |
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| and `x_1,x_2,S_1,S_2,A_1,A_2 >= 0` |
| Tableau-1 | `C_j` | `0` | `0` | `0` | `0` | `1` | `1` | | |
| `C_B` | `"Basis"` | `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` | `"Ratio"=(RHS)/(x_2)` |
| `R_1` `1` | `A_1` | `2` | `1` | `-1` | `0` | `1` | `0` | `4` | `(4)/(1)=4` |
| `R_2` `1` | `A_2` | `1` | `(7)` | `0` | `-1` | `0` | `1` | `7` | `(7)/(7)=1``->` |
| | `Z_j` | `3` | `8` | `-1` | `-1` | `1` | `1` | `Z=11` | |
| | `Z_j-C_j` | `3` | `8``uarr` | `-1` | `-1` | `0` | `0` | | |
Most Positive `Z_j-C_j` is `8`. So,
the entering variable is `x_2`.
Minimum ratio is `1`. So,
the leaving basis variable is `A_2`.
`:.`
The pivot element is `7`.
Entering `=x_2`, Departing `=A_2`, Key Element `=7`
`R_2`(new)`= R_2`(old) `-: 7`
| `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` |
| `R_2`(old) = | `1` | `7` | `0` | `-1` | `0` | `1` | `7` |
| `R_2`(new)`= R_2`(old) `-: 7` | `0.1429` | `1` | `0` | `-0.1429` | `0` | `0.1429` | `1` |
`R_1`(new)`= R_1`(old) - `R_2`(new)
| `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` |
| `R_1`(old) = | `2` | `1` | `-1` | `0` | `1` | `0` | `4` |
| `R_2`(new) = | `0.1429` | `1` | `0` | `-0.1429` | `0` | `0.1429` | `1` |
| `R_1`(new)`= R_1`(old) - `R_2`(new) | `1.8571` | `0` | `-1` | `0.1429` | `1` | `-0.1429` | `3` |
| Tableau-2 | `C_j` | `0` | `0` | `0` | `0` | `1` | `1` | | |
| `C_B` | `"Basis"` | `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` | `"Ratio"=(RHS)/(x_1)` |
| `R_1` `1` | `A_1` | `(1.8571)` | `0` | `-1` | `0.1429` | `1` | `-0.1429` | `3` | `(3)/(1.8571)=1.6154``->` |
| `R_2` `0` | `x_2` | `0.1429` | `1` | `0` | `-0.1429` | `0` | `0.1429` | `1` | `(1)/(0.1429)=7` |
| | `Z_j` | `1.8571` | `0` | `-1` | `0.1429` | `1` | `-0.1429` | `Z=3` | |
| | `Z_j-C_j` | `1.8571``uarr` | `0` | `-1` | `0.1429` | `0` | `-1.1429` | | |
Most Positive `Z_j-C_j` is `1.8571`. So,
the entering variable is `x_1`.
Minimum ratio is `1.6154`. So,
the leaving basis variable is `A_1`.
`:.`
The pivot element is `1.8571`.
Entering `=x_1`, Departing `=A_1`, Key Element `=1.8571`
`R_1`(new)`= R_1`(old) `-: 1.8571`
| `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` |
| `R_1`(old) = | `1.8571` | `0` | `-1` | `0.1429` | `1` | `-0.1429` | `3` |
| `R_1`(new)`= R_1`(old) `-: 1.8571` | `1` | `0` | `-0.5385` | `0.0769` | `0.5385` | `-0.0769` | `1.6154` |
`R_2`(new)`= R_2`(old) - `0.1429 R_1`(new)
| `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` |
| `R_2`(old) = | `0.1429` | `1` | `0` | `-0.1429` | `0` | `0.1429` | `1` |
| `R_1`(new) = | `1` | `0` | `-0.5385` | `0.0769` | `0.5385` | `-0.0769` | `1.6154` |
| `0.1429 xx R_1`(new) = | `0.1429` | `0` | `-0.0769` | `0.011` | `0.0769` | `-0.011` | `0.2308` |
| `R_2`(new)`= R_2`(old) - `0.1429 R_1`(new) | `0` | `1` | `0.0769` | `-0.1538` | `-0.0769` | `0.1538` | `0.7692` |
| Tableau-3 | `C_j` | `0` | `0` | `0` | `0` | `1` | `1` | | |
| `C_B` | `"Basis"` | `x_1` | `x_2` | `S_1` | `S_2` | `A_1` | `A_2` | `RHS` | `"Ratio"` |
| `R_1` `0` | `x_1` | `1` | `0` | `-0.5385` | `0.0769` | `0.5385` | `-0.0769` | `1.6154` | |
| `R_2` `0` | `x_2` | `0` | `1` | `0.0769` | `-0.1538` | `-0.0769` | `0.1538` | `0.7692` | |
| | `Z_j` | `0` | `0` | `0` | `0` | `0` | `0` | `Z=0` | |
| | `Z_j-C_j` | `0` | `0` | `0` | `0` | `-1` | `-1` | | |
Since all `Z_j-C_j <= 0`
Hence, optimal solution is arrived with value of variables as :
`x_1=1.6154,x_2=0.7692`
Min `Z=0`
-->Phase-2<--
we eliminate the artificial variables and change the objective function for the original,
Min `Z=x_1 + x_2 + 0S_1 + 0S_2`
| Tableau-1 | `C_j` | `1` | `1` | `0` | `0` | | |
| `C_B` | `"Basis"` | `x_1` | `x_2` | `S_1` | `S_2` | `RHS` | `"Ratio"` |
| `R_1` `1` | `x_1` | `1` | `0` | `-0.5385` | `0.0769` | `1.6154` | |
| `R_2` `1` | `x_2` | `0` | `1` | `0.0769` | `-0.1538` | `0.7692` | |
| | `Z_j` | `1` | `1` | `-0.4615` | `-0.0769` | `Z=2.3846` | |
| | `Z_j-C_j` | `0` | `0` | `-0.4615` | `-0.0769` | | |
Since all `Z_j-C_j <= 0`
Hence, optimal solution is arrived with value of variables as :
`x_1=1.6154,x_2=0.7692`
Min `Z=2.3846`
This material is intended as a summary. Use your textbook for detail explanation.
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