[docs] Add tutorial on transitioning from MPB

docs/make.jl

@@ -27,6 +27,7 @@ makedocs(
         "Tutorials" => [
             "tutorials/example.md",
             "tutorials/implementing.md",
+            "tutorials/mathprogbase.md",
         ],
         "Manual" => [
             "manual/standard_form.md",

docs/src/tutorials/mathprogbase.md

@@ -0,0 +1,97 @@
+# Transitioning from MathProgBase
+
+MathOptInterface is a replacement for [MathProgBase.jl](https://github.com/JuliaOpt/MathProgBase.jl).
+However, it is not a direct replacement.
+
+## Transitioning a solver interface
+
+Writing a solver interface in MathOptInterface is more work than the equivalent
+interface in MathProgBase.
+
+For more information, read [Implementing a solver interface](@ref).
+
+## Transitioning the high-level functions
+
+MathOptInterface doesn't provide replacements for the high-level interfaces in
+MathProgBase. We recommend you use [JuMP](https://github.com/jump-dev/JuMP.jl)
+as a modeling interface instead.
+
+!!! tip
+    If you haven't used JuMP before, start with the tutorial
+    [Getting started with JuMP](https://jump.dev/JuMP.jl/stable/tutorials/Getting%20started/getting_started_with_JuMP/)
+
+### linprog
+
+Here is one way of transitioning from `linprog`:
+
+```julia
+using JuMP
+
+function linprog(c, A, sense, b, l, u, solver)
+    N = length(c)
+    model = Model(solver)
+    @variable(model, l[i] <= x[i=1:N] <= u[i])
+    @objective(model, Min, c' * x)
+    eq_rows, ge_rows, le_rows = sense .== '=', sense .== '>', sense .== '<'
+    @constraint(model, A[eq_rows, :] * x .== b[eq_rows])
+    @constraint(model, A[ge_rows, :] * x .>= b[ge_rows])
+    @constraint(model, A[le_rows, :] * x .<= b[le_rows])
+    optimize!(model)
+    return (
+        status = termination_status(model),
+        objval = objective_value(model),
+        sol = value.(x)
+    )
+end
+```
+
+### mixintprog
+
+Here is one way of transitioning from `mixintprog`:
+
+```julia
+using JuMP
+
+function mixintprog(c, A, rowlb, rowub, vartypes, lb, ub, solver)
+    N = length(c)
+    model = Model(solver)
+    @variable(model, lb[i] <= x[i=1:N] <= ub[i])
+    for i in 1:N
+        if vartypes[i] == :Bin
+            set_binary(x[i])
+        elseif vartypes[i] == :Int
+            set_integer(x[i])
+        end
+    end
+    @objective(model, Min, c' * x)
+    @constraint(model, rowlb .<= A * x .<= rowub)
+    optimize!(model)
+    return (
+        status = termination_status(model),
+        objval = objective_value(model),
+        sol = value.(x)
+    )
+end
+```
+
+### quadprog
+
+Here is one way of transitioning from `quadprog`:
+
+```julia
+using JuMP
+
+function quadprog(c, Q, A, rowlb, rowub, lb, ub, solver)
+    N = length(c)
+    model = Model(solver)
+    @variable(model, lb[i] <= x[i=1:N] <= ub[i])
+    @objective(model, Min, c' * x + 0.5 * x' * Q * x)
+    @constraint(model, rowlb .<= A * x .<= rowub)
+    optimize!(model)
+    return (
+        status = termination_status(model),
+        objval = objective_value(model),
+        sol = value.(x)
+    )
+end
+```