Gurobi 7.0 solution pool proof of concept via Gurobi.jl

test.jl

using Gurobi, JuMP

# New versions of getvalue, getobjectivevalue for solution pool

"Get the variable values for the `solnumber`th solution in the pool"
function grb_get_xn(m::JuMP.Model, solnumber::Int)
    g = getrawsolver(m)
    Gurobi.set_int_param!(g, "SolutionNumber", solnumber - 1)
    Gurobi.get_dblattrarray(g, "Xn", 1, Gurobi.num_vars(g))
end

"As per `getvalue`, but returns the value for the `solnumber`th solution in the pool"
function JuMP.getvalue(x::Variable, solnumber::Int)
    if solnumber == 1
        return getvalue(x)
    end
    solution = grb_get_xn(x.m, solnumber)
    solution[x.col]
end
function JuMP.getvalue(x::Array{Variable}, solnumber::Int)
    if solnumber == 1
        return getvalue(x)
    end
    solution = grb_get_xn(first(x).m, solnumber)
    
    ret = similar(x, Float64)
    for I in eachindex(x)
        ret[I] = solution[x[I].col]
    end
    ret
end    

"As per `getobjectivevalue`, but returns the value for the `solnumber`th solution in the pool"
function JuMP.getobjectivevalue(m::JuMP.Model, solnumber::Int)
    if solnumber == 1
        return getobjectivevalue(m)
    end
    Gurobi.set_int_param!(g, "SolutionNumber", solnumber - 1)
    Gurobi.get_dblattr(g, "PoolObjVal")
end

# Example from Gurobi.jl readme
m = Model(solver=GurobiSolver())
@variables(m,begin
    0 <= x <= 5
    0 <= y <= 10, Int
    z, Bin
end)
@objective(m, Max, x + 2y + 5z)
@constraint(m, x + y + z <= 10)
@constraint(m, x + 2y + z <= 15)
solve(m)

# Check number of solutions
g = getrawsolver(m)
solcount = Gurobi.get_sol_count(g)

# Get value of optimal solution - these are the same
getvalue([x, y, z])
getvalue([x, y, z], 1)

# Get value of 2nd solution
getvalue([x, y, z], 2)

# Same but for only one variable
getvalue(x, 1)
getvalue(x, 2)

# Get optimal objective value - these are the same
getobjectivevalue(m)
getobjectivevalue(m, 1)

# Get objective value of 2nd solution
getobjectivevalue(m, 2)