Cannot set the starting point for LP

Specific Domains Optimization (Mathematical)
5

Hi and welcome @Aida_Khajavirad

Yeah, as mentioned above some solver do not support initial values for variables. e.g. for GLPK If we call set_start_value before optimize! we only have a warning:

using JuMP, GLPK

model = Model(GLPK.Optimizer)
@variable(model, 0 <= x <= 2)
@variable(model, 0 <= y <= 30)
@objective(model, Max, 5x + 3 * y)
@constraint(model, con, 1x + 5y <= 3)

JuMP.set_start_value(all_variables(model)[1],1.5)
optimize!(model)

┌ Warning: MathOptInterface.VariablePrimalStart() is not supported by
 MathOptInterface.Bridges.LazyBridgeOptimizer{GLPK.Optimizer}. 
This information will be discarded.

However, if we have already optimized our model and we try to use set_start_value again, we have the error you describe:

optimize!(model)
JuMP.set_start_value(all_variables(model)[1],1.5)
ERROR: MathOptInterface.UnsupportedAttribute{MathOptInterfac

One solver you can try if you need to use set_start_value is Ipopt.

using JuMP, Ipopt

model = Model(Ipopt.Optimizer)
@variable(model, 0 <= x <= 2)
@variable(model, 0 <= y <= 30)
@objective(model, Max, 5x + 3 * y)
@constraint(model, con, 1x + 5y <= 3)

JuMP.set_start_value(all_variables(model)[1],1.5)

optimize!(model)

julia> optimize!(model)
This is Ipopt version 3.13.4, running with linear solver mumps.
NOTE: Other linear solvers might be more efficient 
(see Ipopt documentation).

Number of nonzeros in equality constraint Jacobian...:        0
Number of nonzeros in inequality constraint Jacobian.:        2
Number of nonzeros in Lagrangian Hessian.............:        0

However it nicely warns you that “Other linear solvers might be more efficient (see Ipopt documentation).”

I have never used initial values for LP problems though since solvers are so efficient at it, I would like also to know if initial values are common for LP as they are for NLP.

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