How do you recognize an unbounded LP problem in the Simplex Method?
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The dual simplex method is used to solve LP problems where the solution is feasible for the dual but not the primal. It iteratively improves the solution by making it feasible for the primal while maintaining feasibility for the dual, and it’s particularly useful for re-optimizing problems when constraints are added or modified.
An unbounded LP problem is recognized in the Simplex Method when there is no upper limit on the value of the objective function, typically indicated by a pivot column with all positive coefficients and no restrictions on the variables.
An unbounded LP problem in the Simplex Method is recognized when there is no upper limit on the objective function. This is indicated by a positive coefficient in the objective function row and non-positive ratios of RHS values to the entering variable's column coefficients, suggesting that the variable can increase indefinitely without violating constraints.