Graphical methods help visualize special cases in two-variable linear programming by plotting constraints to identify the feasible region and determine optimal solutions at its vertices. They clarify scenarios like unbounded regions, infeasible solutions, and multiple optimal solutions, enhancing understanding of variable interactions.

Graphical methods help visualize special cases in two-variable linear programming problems by plotting the feasible region defined by the constraints. For example, unboundedness can be seen when the feasible region extends infinitely in the direction of optimization. Infeasibility appears as an empty region with no intersection among constraints, while degeneracy is visible when multiple vertices coincide at optimal solutions. This visual representation aids in understanding how these special cases impact the solution.