By default, variables seem to be initialized in Pyomo. Then the solver uses this initial point. Is there a way to not initialize variables in Pyomo and let the solver compute the initial point? I tried to initialized to None but an initial point is still passed to the solver

Here is a simple example:

import pyomo.environ as pyo

model = pyo.ConcreteModel()

model.x = pyo.Var(within=pyo.Reals)

model.objective = pyo.Objective(
        expr=(model.x + 10)**2,
        sense=pyo.minimize)

solver = pyo.SolverFactory('knitroampl')
results = solver.solve(model, tee=True)

Knitro would indicate “No initial point provided” if it was the case:

Knitro presolve eliminated 0 variables and 0 constraints.

concurrent_evals         0
datacheck                0
hessian_no_f             1
hessopt                  1
The problem is identified as unconstrained.

Problem Characteristics                                 (   Presolved)
-----------------------
Objective goal:  Minimize
Objective type:  quadratic
Number of variables:                                  1 (           1)
    bounded below only:                               0 (           0)
    bounded above only:                               0 (           0)
    bounded below and above:                          0 (           0)
    fixed:                                            0 (           0)
    free:                                             1 (           1)
Number of constraints:                                0 (           0)
    linear equalities:                                0 (           0)
    quadratic equalities:                             0 (           0)
    gen. nonlinear equalities:                        0 (           0)
    linear one-sided inequalities:                    0 (           0)
    quadratic one-sided inequalities:                 0 (           0)
    gen. nonlinear one-sided inequalities:            0 (           0)
    linear two-sided inequalities:                    0 (           0)
    quadratic two-sided inequalities:                 0 (           0)
    gen. nonlinear two-sided inequalities:            0 (           0)
Number of nonzeros in Jacobian:                       0 (           0)
Number of nonzeros in Hessian:                        1 (           1)

Knitro using the Interior-Point/Barrier Direct algorithm.

  Iter      Objective      FeasError   OptError    ||Step||    CGits
--------  --------------  ----------  ----------  ----------  -------
       0    1.000000e+02   0.000e+00
       1    0.000000e+00   0.000e+00   0.000e+00   1.000e+01        0

EXIT: Locally optimal solution found.

Final Statistics
----------------
Final objective value               =   0.00000000000000e+00
Final feasibility error (abs / rel) =   0.00e+00 / 0.00e+00
Final optimality error  (abs / rel) =   0.00e+00 / 0.00e+00
# of iterations                     =          1
# of CG iterations                  =          0
# of function evaluations           =          0
# of gradient evaluations           =          0
# of Hessian evaluations            =          0
Total program time (secs)           =       0.00318 (     0.016 CPU time)
Time spent in evaluations (secs)    =       0.00000

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