如何在Pyomo中不初始化变量，让求解器自行计算初始点？

默认情况下Pyomo会自动初始化变量，求解器会基于这个初始点进行计算。有没有办法不让Pyomo初始化变量，转而让求解器自行生成初始点？我试过把变量初始化为None，但还是有初始点被传递给求解器。

以下是测试示例：

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)

按预期，若未提供初始点Knitro应提示"No initial point provided"，但实际运行输出如下：

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

===============================================================================

Pyomo默认会给未显式初始化的变量赋值0作为初始值（从迭代0的目标值100可反推，x初始值为0）。要让求解器自行生成初始点，可通过以下方式实现：

• 设置Knitro专属选项
  直接通过求解器选项告知Knitro不使用Pyomo提供的初始点，或启用其自动初始点生成功能：

solver = pyo.SolverFactory('knitroampl')
# 禁止使用Pyomo传递的初始点
solver.options['initial_point'] = None
# 或开启Knitro自动初始点生成（参数值参考Knitro官方文档）
solver.options['initpoint'] = 2
results = solver.solve(model, tee=True)

• 清空变量初始值并禁用热启动
  先将变量的value设为None，再配合warmstart=False参数避免传递初始值：

model.x.value = None
results = solver.solve(model, tee=True, warmstart=False)

• 通过AMPL接口传递缺失值
  由于使用的是knitroampl（基于AMPL接口），可将变量初始值设为AMPL识别的缺失值，让Knitro知晓无初始点：

model.x = pyo.Var(within=pyo.Reals, initialize=pyo.Param(initialize=None))

若设置正确，Knitro会输出"No initial point provided"，并使用自身逻辑生成初始点开始计算。

内容的提问来源于Stack Exchange，提问作者fontanf