Shadow Price in Linear Programming

Understanding Shadow Price in Linear Programming

Shadow price in linear programming refers to the rate at which the value of the objective function will change with each additional unit of the resource represented by the constraint. It is typically used in sensitivity analysis to understand the value of scarce resources in the optimal solution of linear programming problems.

Parameter usage:

• constraintCoefficient: coefficient of the variable in the constraint (must be a positive number)
• objectiveFunctionCoefficient: coefficient of the variable in the objective function

Output:

• shadowPrice: the change in the value of the objective function per unit change in the constraint

Data validation:

For constraintCoefficient, valid numbers are greater than zero. The objectiveFunctionCoefficient should be a validated number.

Summary

This calculation is crucial for decision-makers who aim to maximize profit or minimize cost, as it indicates which constraints are binding and which resources are most valuable.