What is degeneracy in Linear Programming, and why is it important?
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Degeneracy occurs when more than one solution yields the same optimal value for the objective function at different vertices of the feasible region. It is important because it can cause issues in algorithms like the Simplex method, leading to cycling (revisiting the same solutions) and slowing down the search for the optimal solution.
Degeneracy in linear programming occurs when one or more basic variables are zero at the optimal solution, often due to multiple constraints intersecting at the same point. It is important because it can complicate the solution process, potentially leading to cycling in methods like the Simplex Method. Recognizing degeneracy aids in ensuring efficient optimization and interpreting results, indicating alternative optimal solutions or redundancy in constraints.
Degeneracy in linear programming occurs when a basic feasible solution has one or more basic variables equal to zero. It is important because it can lead to cycling in the Simplex Method, where the algorithm may revisit the same solutions without making progress. This can complicate the convergence to an optimal solution.
Degeneracy in linear programming occurs when a basic feasible solution has basic variables equal to zero. It's important because it can lead to multiple optimal solutions or cycles in the simplex method, affecting algorithm efficiency