Eli Towle
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Recent activity by Eli Towle-
Hi Hans, Are any of the piecewise linear functions convex (assuming you're minimizing)? If so, you can instead use a more efficient linear formulation to model the piecewise linear function. This i...
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Hi Fan, The MIPNODE callback is called once for each cut pass that occurs at the root node. This is described in more detail in the callback codes documentation. I hope this helps. Thanks! Eli
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Hi Hans, There is no way to use piecewise linear objectives with setObjectiveN(). However, you can add piecewise linear constraints (see here), and then set the multiple objectives to be the variab...
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Hi Suhas, The scipy.optimize.newton method finds a zero of the given function. This is different from what is meant by the optimization problem in your code. As written, the goal of your optimizati...
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Hi Vaibhav, Okay, thanks for the clarification. With (1), there are still variables in the constraint, because the Vpredicted linear expression includes the Rl, Rm, and Rh variables. It seems that ...
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Hi Vaibhav, First, I'll clarify a few general concepts related to optimization. The line vulvar=m.addVars(len(Vul), vtype=GRB.CONTINUOUS, obj=Vul,name="vul") adds a number of nonnegative continuous...
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Hi Mirna, For numerical reasons, an integrality constraint on a variable is considered satisfied if the variable value is "close enough" to an integer. By default, this tolerance is 1e-5. You can t...
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Hi Niccolò, Here is a simple example showing how to set the Lazy attribute after creating the constraints. # addConstrs() returns tupledict of constraintsmyconstrs = m.addConstrs(x[i] + y[i] <= 1 f...
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Hi Kamal, This can be done as follows: optimizer = SolverFactory('gurobi')optimizer.options['threads'] = 1 For more information about passing options to solvers, see the Pyomo documentation on the ...
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Hi Austin, I'll assume you're asking about "lazy constraints" as opposed to "user cuts." For more information on the difference between these two, see this article. Lazy constraints are required fo...