Hi, thank you very much for your response!
I have been trying to solve an LP with the dual simplex method. I’d like to have a warm start that is not necessarily feasible. I’ll provide a simple code example that shows what I’m trying to do.
model = Model(Gurobi.Optimizer)
@variable(model, x[1:2] >= 0)
@objective(model, Max, 2*x + x)
@constraint(model, c1, x <= 1)
@constraint(model, c3, x <= 1)
set_optimizer_attribute(model, “Method”, 1) #use dual simplex
set_optimizer_attribute(model, “Presolve”, 0)
The output indicates that the warm start is being ignored. I tried to work around this by adding a superfluous binary variable to the model. This actually worked, and seemed to provide warm starts given that they were feasible. However, when I tried to provide an infeasible initial solution (1.5, 1.5), an error message appears indicating that the warm start is being ignored:
“User MIP start did not produce a new incumbent solution
User MIP start violates constraint R0 by 0.500000000”
Also, regarding PStart - I will try setting the DStart values as well as the previous user suggested. However, it seems like the attribute is unrecognized. When I try “x.Start(0.5)” I get the error message “type VariableRef has no field Start”, and a similar message when trying to use PStart.
Thanks again for you help and advice!