Model logs shows Numerical Issues how to handle this
AnsweredThe model log tells, Consider reformulating model. Here how to find which part of the constraint I need to reformulate. Is there any way to see which constraints are causing this issue?
Model contains large matrix coefficient range what is this meaning. How to know which one are large?
It also tells max constraint violation and max general constraint violation, how to know which constraints are violating.

Can you try upgrading to v11.0.0 and rerunning this test?
Cheers,
David0 
David Torres Sanchez We do have v11.0 lic I will do. In general just want to understand below points
Model contains large matrix coefficient range what is this meaning. How to know which one are large?
It also tells max constraint violation and max general constraint violation, how to know which constraints are violating.
The model log tells, Consider reformulating model. Here how to find which part of the constraint I need to reformulate. Is there any way to see which constraints are causing this issue?
0 
Hi Sudheer,
This is the code snippet I use (which uses Python and pandas)
import pandas as pd
import numpy as np
# assumes your model is "m"
A = np.abs(m.getA()).tocoo() # absolutevalue coefficent matrix in scipy sparse coo_matrix form
cons = np.array(m.getConstrs())
df = pd.DataFrame({
"abscoeff":A.data,
"constr":cons[A.row],
})
# try to find family of constraints with highest magnitude of coefficients
# (you obviously need to tailor this to the coefficients in your model)
df["name"] = df["constr"].map(lambda c: c.constrname) # add names
df["family"] = df["name"].map(lambda n: n.split("_")[0]) # assuming name is of the form myconstr_0_1
df.query("abscoeff > 8e6")["family"].value_counts()
# try to find family of constraints with smallest magnitude of coefficients
df.query("abscoeff < 1e3")["family"].value_counts()
# investigate violated constraints
# note this is only looking at linear constraints
slacks = m.getAttr("Slack", cons)
df2 = pd.DataFrame({
"violation":slacks[slacks < 0],
"constr":cons[slacks < 0],
})
# can sort df2, add names, count family etcFor guidance on reducing the coefficient range please see the subsections of Tolerances and User Scaling (a section in our Guidelines for Numerical Issues chapter of our reference manual).
 Riley
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