JuMP in julia

Specific Domains Optimization (Mathematical)
, , ,
9

I see your confusion. JuMP and MATLAB are very different in how they model linear programs.

x_sol = linprog(c, A, b, [], [], lb, ub, [], opt)

# is equivalent to

using JuMP, HiGHS
model = Model(HiGHS.Optimizer)
@variable(model, lb[i] <= x[i=1:length(c)] <= ub[I])
@objective(model, Min, c' * x)
@constraint(model, A * x .<= b)
optimize!(model)
x_sol = value.(x)

I think you’re looking for something like


using JuMP, HiGHS, LinearAlgebra
c = DRe + 0.6DBla + 0.6DBO
model = Model(HiGHS.Optimizer)
@variable(model, 0 <= x[i=1:length(c)] <= 50)
@objective(model, Min, dot(c, x))
@constraint(model, PTV68 * x .<= -1)
optimize!(model)
x_sol = value.(x)
1 Like