<P> Without the constraints, the solution would be (0, 0), where f (x) (\ displaystyle f ((\ mathbf (x)))) has the lowest value . But this solution does not satisfy the constraints . The solution of the constrained optimization problem stated above is x = (1, 1) (\ displaystyle (\ mathbf (x)) = (1, 1)), which is the point with the smallest value of f (x) (\ displaystyle f ((\ mathbf (x)))) that satisfies the two constraints . </P> <Ul> <Li> If an inequality constraint holds with equality at the optimal point, the constraint is said to be binding, as the point cannot be varied in the direction of the constraint even though doing so would improve the value of the objective function . </Li> <Li> If an inequality constraint holds as a strict inequality at the optimal point (that is, does not hold with equality), the constraint is said to be non-binding, as the point could be varied in the direction of the constraint, although it would not be optimal to do so . If a constraint is non-binding, the optimization problem would have the same solution even in the absence of that constraint . </Li> <Li> If a constraint is not satisfied at a given point, the point is said to be infeasible . </Li> </Ul> <Li> If an inequality constraint holds with equality at the optimal point, the constraint is said to be binding, as the point cannot be varied in the direction of the constraint even though doing so would improve the value of the objective function . </Li> <Li> If an inequality constraint holds as a strict inequality at the optimal point (that is, does not hold with equality), the constraint is said to be non-binding, as the point could be varied in the direction of the constraint, although it would not be optimal to do so . If a constraint is non-binding, the optimization problem would have the same solution even in the absence of that constraint . </Li>

What does it mean for a constraint to be binding