To handle unbounded solutions in Linear Programming, first, verify the model's constraints to identify why the feasible region allows unlimited growth of the objective function. If an unbounded solution is confirmed, consider adding constraints to limit the solution space or reformulating the problem to better define boundaries. Alternatively, check for errors in the formulation, as an unbounded solution may indicate that the model does not accurately reflect the real-world situation. If feasible, implement new constraints that restrict the direction in which the objective function can increase.

To handle unbounded solutions, you can introduce constraints to limit the feasible region or reformulate the problem to ensure boundedness.

To handle unbounded solutions, first identify the source of unboundedness in your problem. Next, consider adding constraints to limit the feasible region. You can also reformulate the objective function or use bounded variables to control the solution space. Finally, employ sensitivity analysis to understand how adjustments affect boundedness.