Take this quadratic constraint as example:
(-x1^2 + x2^2 + x3^2 <= 0)
Note that in the CPLEX Python API, the above constraint is formalated as follows:
m.quadratic_constraints.add(
quad_expr=[["x1", "x2", "x3"], ["x1", "x2", "x3"], [-1, 1, 1]],
sense='L', rhs=0, name="q1"
)
How to add the aforementioned quadratic constraint into the model by using DOcplex, not CPLEX Python API?
let me change a bit the example I shared in cpleqp equivalent in docplex
from docplex.mp.model import Model
mdl = Model(name='qpex1')
#decision variables
x = {b: mdl.continuous_var(0,40,name="x"+str(b)) for b in range(0,3)}
# Constraint
mdl.add_constraint( - x[0] + x[1] + x[2] <= 20, 'ct1')
mdl.add_constraint(x[0] - 3 * x[1] + x[2] <= 30,'ct2')
mdl.add_constraint(x[0] * x[0] <= 30,'quad')
# Objective
mdl.maximize(x[0] + 2 * x[1] + 3 * x[2]-\
0.5 * ( 33*x[0]*x[0] + 22*x[1]*x[1] + 11*x[2]*x[2] -\
12*x[0]*x[1] - 23*x[1]*x[2] ))
msol=mdl.solve()
# Dislay solution
for v in mdl.iter_continuous_vars():
print(v," = ",v.solution_value)
print("objective : ",msol.get_objective_value() )
and
mdl.add_constraint(x[0] * x[0] <= 30,'quad')
is a quadratic constraint