我想用我的numpy数组A和b向Pyomo模型中添加约束Ax=b，但不幸的是，目前的性能非常差。

import time
    import numpy as np
    import pyomo.environ as pyo

    start = time.time()
    rows = 287
    cols = 2765
    A = np.random.rand(rows, cols)
    b = np.random.rand(rows)
    mdl = pyo.ConcreteModel()
    mdl.rows = range(rows)
    mdl.cols = range(cols)
    mdl.A = A
    mdl.b = b
    mdl.x_var = pyo.Var(mdl.cols, bounds=(0.0, None))

    mdl.constraints = pyo.ConstraintList()
    [mdl.constraints.add(sum(mdl.A[row, col] * mdl.x_var[col] for col in mdl.cols) <= mdl.b[row]) for row in mdl.rows]

    mdl.obj = pyo.Objective(expr=sum(mdl.x_var[col] for col in mdl.cols), sense=pyo.minimize)
    end = time.time()
    print(end - start)

由于add语句和大量的列，is几乎需要30秒，是否可以直接快速传递A、x和b，而不是逐行添加？