About JuMP.is_solved_and_feasible

odow · March 12, 2025, 7:24pm

Is there a question here?

is_solved_and_feasible does what it says it does: did the solver run successfully and find a feasible solution?

You can see the implementation here:

src/optimizer_interface.jl

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          """
              is_solved_and_feasible(
                  model::GenericModel;
                  allow_local::Bool = true,
                  allow_almost::Bool = false,
                  dual::Bool = false,
                  result::Int = 1,
              )
          
          Return `true` if:
           * the [`termination_status`](@ref) is one of:
             * [`OPTIMAL`](@ref) (the solver found a global optimum)
             * [`LOCALLY_SOLVED`](@ref) (the solver found a local optimum, which may also
               be the global optimum, but the solver could not prove so).
           * the [`primal_status`](@ref) of the result index `result` is `FEASIBLE_POINT`.
          
          This function is conservative, in that it returns `false` for situations like
          the solver terminating with a feasible solution due to a time limit.
          
          If this function returns `false`, use [`termination_status`](@ref),

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I should remove has_values from the documentation. It is misleading. It doesn’t confirm that there is a feasible primal solution, only that the primal status is not NO_SOLUTION. The result might be an INFEASIBLE_POINT, or a NEARLY_FEASIBLE_POINT… neither are probably what you are expecting.

github.com/jump-dev/JuMP.jl

src/variables.jl

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          """
              has_values(model::GenericModel; result::Int = 1)
          
          Return `true` if the solver has a primal solution in result index `result`
          available to query, otherwise return `false`.
          
          See also [`value`](@ref) and [`result_count`](@ref).
          
          ## Example
          
          ```jldoctest
          julia> import HiGHS
          
          julia> model = Model(HiGHS.Optimizer);
          
          julia> set_silent(model)
          
          julia> @variable(model, x);
          
          julia> @constraint(model, c, x <= 1)

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About JuMP.is_solved_and_feasible

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