BuMP to JuMP v0.22 (#489)

Project.toml

@@ -1,7 +1,7 @@
 name = "SDDP"
 uuid = "f4570300-c277-11e8-125c-4912f86ce65d"
 authors = ["Oscar Dowson <[email protected]"]
-version = "0.4.3"
+version = "0.4.4"
 
 [deps]
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
@@ -19,12 +19,12 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 
 [compat]
-GLPK = "0.14"
+GLPK = "0.15"
 HTTP = "0.8.1, 0.9"
 JSON = "0.21"
-JSONSchema = "0.3"
-JuMP = "0.21"
-MutableArithmetics = "0.2"
+JSONSchema = "1.0"
+JuMP = "0.22"
+MutableArithmetics = "0.3"
 RecipesBase = "1"
 Reexport = "0.2, 1"
 TimerOutputs = "0.5"

docs/src/guides/debug_a_model.md

@@ -116,7 +116,6 @@ CachingOptimizer state: EMPTY_OPTIMIZER
 Solver name: GLPK
 
 julia> set_silent(det_equiv)
-true
 
 julia> optimize!(det_equiv)
 

docs/src/tutorial/theory/21_theory_intro.jl

@@ -116,11 +116,12 @@ function kelleys_cutting_plane(
     JuMP.@variable(model, θ >= lower_bound)
     JuMP.@variable(model, x[1:input_dimension])
     JuMP.@objective(model, Min, θ)
+    x_k = fill(NaN, input_dimension)
     lower_bound, upper_bound = -Inf, Inf
     while true
         ## Step (2):
         JuMP.optimize!(model)
-        x_k = JuMP.value.(x)
+        x_k .= JuMP.value.(x)
         ## Step (3):
         lower_bound = JuMP.objective_value(model)
         upper_bound = min(upper_bound, f(x_k))
@@ -138,7 +139,7 @@ function kelleys_cutting_plane(
             break
         end
     end
-    println("Found solution: x_K = ", JuMP.value.(x))
+    println("Found solution: x_K = ", x_k)
     return
 end
 

src/JuMP.jl

@@ -101,8 +101,6 @@ function JuMP.add_variable(
     return state
 end
 
-JuMP.variable_type(model::JuMP.Model, ::Type{State}) = State
-
 function JuMP.value(state::State{JuMP.VariableRef})
     return State(JuMP.value(state.in), JuMP.value(state.out))
 end

test/electric.sof.json

@@ -1 +1 @@
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