Simplex Method Steps (Rule)

Step1:

Formulate the Problem
a. Formulate the mathematical model of the given linear programming problem.
b. If the objective function is minimization type then change it into maximization type.
Min z =  Max (z)
c. All the `X_(B_i) > 0`. So if any `X_(B_i) < 0` then multiply the corresponding constraint by 1 to make `X_(B_i) > 0`. So sign `<=` changed to `>=` and vice varsa
d. Transform every `<=` constraint into an `=` constraint by adding a slack variable to every constraint and assign a 0 cost coefficient in the objective function.

Step2:

Find out the Initial basic solution
Find the initial basic feasible solution by setting zero value to the decision variables. That shown in the example1

Step3:

Test for Optimality
a. Calculate the values of `c_j  z_j` in the last row of simplex table.
b. If all `c_j  z_j <= 0` , the current basic feasible solution is the optimal solution.
c. In `c_j  z_j > 0`, then select the variable that has largest `c_j  z_j` and enter this variable into the new table. This column is called key column (pivot column).

Step4:

Test for Feasibility (variable to leave the basis)
a. Find the ratio by dividing the values of `X_B` column by the positive values of key column (say `a_(ij)>0`)
b. Find the minimum ratio and this row is called key row (pivot row) and corresponding variable will leave the solution.
c. The intersection element of key row and key column is called key element (pivot element).

Step5:

Determine the new solution
a. The new values of key row can be obtained by dividing the key row elements by the pivot element.
eg. `R_1`(new)`=``R_1`(old) `:3`
b. The numbers in the remaining rows can be computed by utilizing the following formula:
Row(new) = Row(old)  (value of key column and Row(old)) `xx` KeyRow(new)
eg. `R_2`(new)`=``R_2`(old) ` 2` `R_1`(new)

Step6:

Repeat the procedure
Goto step 3 and repeat the procedure until all the values of `c_j – z_j<=0`.
