moved test case and added changelog (#196)

* moved test case and added to changelog
* v0.6.4

CHANGELOG.md

@@ -1,8 +1,9 @@
 # Juniper.jl Changelog
 
-### Unregistered
+### v0.6.4
 - Use of `JUNIPER_RNG` for random numbers. Makes sure that `rand` outside of Juniper is unaffected.
 - Option to set the random seed with the option `seed`.
+- Bugfix: Generating the real nlp in the feasibility pump failed when there was no objective. [Issue #195](https://github.com/lanl-ansi/Juniper.jl/pull/195)
 
 ### 0.6.3
 - Bugfix: `registered_functions` failed in feasibility pump [Issue #189](https://github.com/lanl-ansi/Juniper.jl/pull/189)

Project.toml

@@ -2,7 +2,7 @@ name = "Juniper"
 uuid = "2ddba703-00a4-53a7-87a5-e8b9971dde84"
 authors = ["Ole Kröger <[email protected]>", "Kaarthik Sundar [email protected]"]
 repo = "https://github.com/lanl-ansi/Juniper.jl.git"
-version = "0.6.3"
+version = "0.6.4"
 
 [deps]
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"

test/basic.jl

@@ -1207,23 +1207,4 @@ end
     @test JuMP.value(a_var) ≈ 1
 end
 
-@testset "Issue 195: FPump without objective" begin
-    ipopt_solver = JuMP.optimizer_with_attributes(Ipopt.Optimizer, "print_level" => 0, "sb" => "yes", "max_iter" => 50000)
-    cbc_solver = JuMP.optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-    juniper_solver = JuMP.optimizer_with_attributes(Juniper.Optimizer,
-        "nl_solver" => ipopt_solver,
-        "mip_solver" => cbc_solver, "log_levels" => [])
-    m = Model(juniper_solver)
-    @variable(m, x[1:3], Int)
-    @variable(m, y)
-    @NLconstraint(m, x[1]*x[2]*x[3]*y >= 5)
-    optimize!(m)
-
-    for i=1:3
-        xval = JuMP.value(x[i])
-        @test isapprox(round(xval)-xval, 0; atol=sol_atol)
-    end
-    @test JuMP.objective_value(m) ≈ 0.0
-end
-
 end

test/fpump.jl

@@ -248,4 +248,27 @@ end
     @test status == MOI.LOCALLY_SOLVED || status == MOI.TIME_LIMIT
 end
 
+@testset "FP: Issue 195: FPump without objective" begin
+    println("==================================")
+    println("FP: Issue 195: FPump without objective")
+    println("==================================")
+
+    ipopt_solver = JuMP.optimizer_with_attributes(Ipopt.Optimizer, "print_level" => 0, "sb" => "yes", "max_iter" => 50000)
+    cbc_solver = JuMP.optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+    juniper_solver = JuMP.optimizer_with_attributes(Juniper.Optimizer,
+        "nl_solver" => ipopt_solver,
+        "mip_solver" => cbc_solver, "log_levels" => [])
+    m = Model(juniper_solver)
+    @variable(m, x[1:3], Int)
+    @variable(m, y)
+    @NLconstraint(m, x[1]*x[2]*x[3]*y >= 5)
+    optimize!(m)
+
+    for i=1:3
+        xval = JuMP.value(x[i])
+        @test isapprox(round(xval)-xval, 0; atol=sol_atol)
+    end
+    @test JuMP.objective_value(m) ≈ 0.0
+end
+
 end