Panggah Prabawa
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Latest activity by Panggah Prabawa
Panggah Prabawa commented,
Hi, Ryuta, Sweet. Thank you for your explanation! Best, Panggah.

Panggah Prabawa commented,
Hi, Ryuta, It can be applicable too, however, I will apply the function iteratively so it may not be easy to write down all the variables that are going to be packed. Does Gurobi provide a way to a...

Panggah Prabawa created a post,
Passing multiple variables across Python function/methods
AnsweredHi all, I wonder if I can pass multiple/all variables across Python functions considering many variables to pass on so that they are accessible and optimized outside the function. For example: def ...

Panggah Prabawa commented,
Hi Jaromił, Thank you for the information.Anyways, is it possible to set a starting point like a local solver does? Best, Panggah.

Panggah Prabawa commented,
Hi Jaromił, To compare with the previous example (problem A), I implemented another example (problem B) below: Both problems have the same log:"Continuous model is nonconvex  solving as a MIP" ...

Panggah Prabawa commented,
Hi, Jaromił. Thank you for your reply. For now, I have a continuous nonlinear problem with multiple bilinear terms. I believe that this problem may have multiple local optima. However, the Solution...

Panggah Prabawa created a post,
Treating Gurobi as a local solver?
AnsweredHi all, As Gurobi is a global solver, is it possible to make Gurobi solve a problem and stop when it finds a local optimum by e.g., adding model.Param? I intend to make an iterative algorithm using...

Panggah Prabawa created a post,
Convex vs SOCP Constraint
AnsweredHello, I am constructing a problem which includes a convex constraint: \( l_{ij} * u_{i} \geq p_{ij}^2 + q_{i,j}^2 \) which I coded as follows (with additional dimension \( t \) ): Ohm_law = m.addC...

Panggah Prabawa commented,
Thank you for your answers, Jaromil and Riley.I will test the creation speeds of those options. Very interesting.

Panggah Prabawa commented,
Thank you for your response. I know that is a way to do that.Let's say that the index is a tuple (i,j,t), where t < T.I maintain parameter coeff to have 2 key lengths to avoid iterating coeff over ...