How is sensitivity analysis applied to integer programming?
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Sensitivity analysis in integer programming is applied using techniques like shadow prices, integer sensitivity analysis, parametric integer programming, scenario analysis, and robust optimization to assess the impact of changes on integer variables and constraints.
Sensitivity analysis in integer programming is applied by:
- Evaluating Objective Coefficients: Analyzing how changes in objective coefficients impact the optimal integer solution.
- Assessing Constraint Changes: Determining the effect of modifying constraints on the feasible integer solutions.
- Exploring Feasibility: Identifying how small changes can influence the integer feasibility of solutions.
- Utilizing Rounding Effects: Understanding how rounding in solutions can affect overall outcomes.
This helps in making informed decisions while considering the discrete nature of integer variables.