Add a quadratic constraint to a model.
Important note: the algorithms that Gurobi uses to solve quadratically constrained problems can only handle certain types of quadratic constraints. Constraints of the following forms are always accepted:
- , where is Positive Semi-Definite (PSD)
- , where is a vector of variables, and is a non-negative variable (a Second-Order Cone)
- , where is a vector of variables, and and are non-negative variables (a rotated Second-Order Cone)
Note that this method also accepts a TempConstr as its first argument (with the name as its second argument). This allows you to use operator overloading to create constraints. See TempConstr for more information.
sense: Sense for new quadratic constraint (GRB.LESS_EQUAL or GRB.GREATER_EQUAL).
name: Name for new constraint.
New quadratic constraint object.
model.addQConstr(x*x + y*y, GRB.LESS_EQUAL, z*z, "c0") model.addQConstr(x*x + y*y <= 2.0, "c1")