Advanced features

objectivevaluemagnitude(m::JuMP.Model, magnitude)

Set the magnitude of the objective function of the model m to magnitude

objectivevaluelowerbound(m::JuMP.Model, lb)

Set the lower bound of the objective function of the model m to lb

objectivevalueupperbound(m::JuMP.Model, ub)

Set the upper bound of the objective function of the model m to ub

branchingpriorityinmaster(x::JuMP.JuMPContainer, subproblem::Tuple{Symbol, Union{Tuple, Integer}}, priority)

Assign to the variables x defined in the subproblem subproblem the priority value priority in master.

branchingpriorityinmaster(x, (:B_SP, 1), 2)

The variable x defined in the Benders subproblem with id 1 will have the branching priority value 2in the master.

branchingpriorityinsubproblem(x::JuMP.JuMPContainer, subproblem::Tuple{Symbol, Union{Tuple, Integer}}, priority)

Assign to the variables x defined in the subproblem subproblem the priority value priority in subproblems.

branchingpriorityinsubproblem(x, (:B_SP, 1), 2)

The variable x defined in the Benders subproblem with id 1 will have the branching priority value 2in subproblems.

addbranching(model::JuMP.Model, rule::Symbol, varname::Symbol; args...)

create a branching rule named rule on variable varname. Agruments are provided by the used and store in an array of pair. Arguments are checked by the solver.