Maliheh Aramon

Hi Ilya,  The parameters ImproveStartGap, ImproveStartNodes, and ImproveStartTime trigger solution improvement strategies where the Gurobi Optimizer only focuses on improving the incumbent to find ...

Hi Ahmad,  After setting the parameter SolutionNumber to the \(i\)-th best solution, the value of each variable can be accessed by querying the attribute Xn and not X (this attribute always reports...

Hi Hadi,    You can define a Gurobi quadratic expression object (GRBQuadExpr) and iterate through the terms in the GRBLinExpr object already defined and multiply each term by the binary variable \(...

  Hi Taylor,    Problem constraints define the feasible search space and the order by which you implement them does not matter.    The two implementation above are the same. Can you please elaborat...

Hi Jose,   No, you cannot. The Var.setAttr() method sets the value of a variable attribute. The GRB.Callback.MIPSOL_OBJBND is not an attribute of a Var object. It is a piece of information that can...

Hi WI,  You need a few changes. Please see below. import gurobipy as gpfrom gurobipy import GRBfrom math import sqrtif __name__ == "__main__": model = gp.Model("name") Var = model.addV...

Hi WI,  Thanks for the response. Sure, I get that your decision variables represent the Euclidean distance between pairs of points (let us refer to them as \(x\) for simplicity) on a grid of 1 by 1...

Hi Ivana,    You need to change the lower bound of the variable \(\texttt{alfa}\) when you are defining it. Specifically, you need to change: alfa= m.addMVar(1, name="alfa") to: alfa= m.addMVar(1...

Hi Ivana,  Running the script above gives the optimal solution of 0 as expected. All decision variables are defined to be non-negative and the only solution that satisfies the last constraint (the ...

Hi Antoine,  The first error occurs because Gurobi does not directly support multiplication of three variables. Please have a look at How do I model multilinear terms in Gurobi? article that expla...