JuMP optimization problem

General Usage
1

I want to write a function

2

Hey there! I think you need to actually run the optimization with optimize!(model) to get a solution

Unless something else isn’t working? I haven’t tried to run your code

See here: Getting started with JuMP · JuMP

4

Could you be a little more precise as to what “not working” means to you? It would make it easier to help :slight_smile:

5

This is not valid Julia syntax, it should be optimize!(model). Was that the issue?

7

Ok, but do you see an error or a wrong result? What do you get? How do you know the true value?

At first glance you still need to specify an optimizer for the code to run

8

After adding an optimizer and fixing a few syntax mistakes, I get 12 instead of 14. Are you sure about your values?

julia> using JuMP, HiGHS

julia> costs = Dict("A" => [2.0, 2.0, 2.0], "B" => [3.0, 3.0, 3.0],);

julia> capacity = Dict("A" => [2.0, 2.0, 1.0], "B" => [1.0, 2.0, 4.0],);

julia> demand = [2.0, 1.0, 3.0];

julia> function op(capacity, costs, demand, optimizer)
           C = keys(capacity)
           D = keys(demand)
           m1 = Model(optimizer)
           @variable(m1, 0 <= x[c in C, d in D])
           @objective(m1, Min, sum(costs[c][d] * x[c, d] for c in C, d in D))
           @constraint(m1, [d in D], sum(x[c, d] for c in C) >= demand[d])
           optimize!(m1)
           print(m1)
           return m1
       end
op (generic function with 1 method)

julia> m1 = op(capacity, costs, demand, HiGHS.Optimizer);
Running HiGHS 1.5.3 [date: 1970-01-01, git hash: 45a127b78]
Copyright (c) 2023 HiGHS under MIT licence terms
Presolving model
3 rows, 6 cols, 6 nonzeros
0 rows, 0 cols, 0 nonzeros
Presolve : Reductions: rows 0(-3); columns 0(-6); elements 0(-6) - Reduced to empty
Solving the original LP from the solution after postsolve
Model   status      : Optimal
Objective value     :  1.2000000000e+01
HiGHS run time      :          0.00
Min 3 x[B,1] + 3 x[B,2] + 3 x[B,3] + 2 x[A,1] + 2 x[A,2] + 2 x[A,3]
Subject to
 x[B,1] + x[A,1] ≥ 2
 x[B,2] + x[A,2] ≥ 1
 x[B,3] + x[A,3] ≥ 3
 x[B,1] ≥ 0
 x[A,1] ≥ 0
 x[B,2] ≥ 0
 x[A,2] ≥ 0
 x[B,3] ≥ 0
 x[A,3] ≥ 0

julia> println(termination_status(m1))
OPTIMAL

julia> println(objective_value(m1))
12.0

julia> println(value.(m1[:x]))
2-dimensional DenseAxisArray{Float64,2,...} with index sets:
    Dimension 1, ["B", "A"]
    Dimension 2, [1, 2, 3]
And data, a 2×3 Matrix{Float64}:
 0.0  0.0  0.0
 2.0  1.0  3.0
11

Have you tried running my corrected code? There were a few typos in yours, for instance you did for c in c whereas you should have separated the key from the key set

13

The code I gave you runs on my computer, did you change the other bits too?