What are the limitations of linear programming models?
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Linear programming models face limitations such as the assumption of linear relationships, the requirement for certainty and static conditions, dependence on precise data, challenges in complex problem formulation, and the focus on a single objective function, which may not suit real-world scenarios.
Linear programming models face limitations such as the assumption of linearity, which may not represent real-world complexities, and reliance on certainty, requiring known and constant parameters. They also mandate divisibility, restricting applicability to fractional values, and impose non-negativity constraints that may not reflect all situations. These factors can limit the models' versatility in decision-making.