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Kuhn-Tucker Conditions for Maximizing objective functions when the constraint is an inequality.

For Maximization subject to  the constraint: g(x,y) =>0,

1.    If  lambda<0, the constraint is a real limitation, and the desired optimum has not been determined.

2.    If lambda =>0, the constraint is not a limitation. Maximize the objective function by itself.

For Maximization subject to  the constraint: g(x,y) =<0,

1.    If  lambda = or > 0, the constraint is a real limitation, and the desired optimum has not been determined.

2.    If lambda < 0, the constraint is not a limitation. Maximize the objective function by itself.

For Minimization subject to  the constraint: g(x,y) = >0,

1.    If  lambda = or > 0, the constraint is a real limitation, and the desired optimum has not been determined.

2.    If lambda < 0, the constraint is not a limitation. Maximize the objective function by itself.