For a non-binding constraint of a maximization linear programming, the increase in shadow price:Group of answer choiceswill increase the objective function value.will decrease the objective function value.will not change the objective function value.might increase or decrease the objective function value.
Question
For a non-binding constraint of a maximization linear programming, the increase in shadow price:Group of answer choiceswill increase the objective function value.will decrease the objective function value.will not change the objective function value.might increase or decrease the objective function value.
Solution
The answer is "will not change the objective function value."
Explanation:
In linear programming, a non-binding constraint is one that does not affect the optimal solution. This means that even if the constraint is changed, the optimal solution (and therefore the value of the objective function) will remain the same.
The shadow price, or dual value, of a constraint in linear programming measures how much the value of the objective function will change if the right-hand side of the constraint is increased by one unit. However, for a non-binding constraint, the shadow price is zero. This is because changing a non-binding constraint does not change the feasible region or the optimal solution.
Therefore, an increase in the shadow price of a non-binding constraint will not change the value of the objective function.
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