Given the following tableau for a max LP
\begin{array}{|c|c|c|c|} \hline & \text{z} & x_1 & x_2 & x_3 & x_4 & x_5 & x_6 & \text{RHS} \\ \hline \text{z} & 1 & c_1 & 0 & c_3 & 0 & 0 & 0 & 13\\ \hline x_2 & 0 & -4 & 1 & a_1 & 0 & a_2 & 0 & \text{b}\\ \hline x_4 & 0 & -1 & 0 & -5 & 1 & -1 & 0 & 3\\ \hline x_6 & 0 & a_3 & 0 & 3 & 0 & -4 & 1 & 2\\ \hline \end{array}
I trying to understand how this tableau works.
First of all, the tableau corresponds to the basic solution given by
$ {\bf x} = (0,b,0,3,0,6)$ Meaning that this is feasible, a BFS, only if $b \geq 0$ for which otherwise $(b\lt0)$ would be infeasible. If I want it to be degenerate, then $ b \gt 0$.
What condition do we have to impose on the unknowns for the problem to be unbounded?
Now, if the current solution is feasible but the objective function can be improved by replacing $x_6$ as basic variable by $x_3$, what condition show we impose on the unknowns?
try:
First of all, we need $b \geq 0$ for feasibility. If we want $x_3$ to leave the basis, we pivot on the column given by the vector $(c_3, a_1, -5, 3)^T$. For the ratio test, we need to find $\min \{c_3/a_1, -5/3, 2/4\}$ meaning that $a_1 \neq 0$ for which otherwise cannot perform the min ratio test, and $c_3$ can be anything. Is this correct?