Computing the Optimal Simplex Tableau for Linear Programming

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I am learning in my class about computing the optimal simplex tableau. I learned that, if you have an initial basic feasible solution, you can apply a series of formulas to compute the optimal tableau.

When you have $m$ basic variables in your BFS and $m$ constraints, I understand how these formulas work.

However, let's say you have $m-1$ basic variables. Then, your $B$ matrix will not be square, and its inverse is not well defined. How do you deal with situations like these?