Sensitivity Analysis & Dual Validation

Linear programming problems often require various approximations to represent real-world scenarios accurately. Companies may find it more practical to introduce additional constraints at a later stage of the process, rather than creating an entirely new model. By leveraging sensitivity analysis, it becomes possible to assess the implications of integrating new constraints into the existing model. Furthermore, certain parameter values, such as resource capacities and objective function coefficients, are typically based on rough estimates. These values are subject to change over time due to fluctuations in costs or variations in resource availability. Conducting sensitivity analysis enables the identification of critical parameters that significantly impact optimality when there are minor alterations in the availability of unit resources

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