What are special cases in Linear Programming (LP)?
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Special cases in LP refer to situations that arise during the formulation or solution of LP problems, which require special attention. These cases include:
- Unbounded solutions
- Infeasibility
- Multiple optimal solutions (degeneracy)
- Redundant constraints
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Special cases in Linear Programming include situations like infeasibility, where no solution exists that satisfies all constraints; unboundedness, where the objective function can increase indefinitely without reaching a maximum; and degeneracy, where multiple optimal solutions exist due to overlapping constraints. These cases can complicate the solution process and require specific techniques to address them effectively.
Special cases in linear programming include unbounded solutions (indefinite objective function values), infeasible solutions (no feasible variable sets), multiple optimal solutions (various combinations yielding the same optimal value), and degenerate solutions (basic variables equal to zero). Identifying these cases is crucial for effective problem-solving and informed decision-making in optimization.
Special cases in linear programming including the Degenerate solutions with a Multiple optimal solutions, Unbounded solutions that the objective can increase indefinitely and a I nfeasible solutions that has no feasible region exists.