Apply suggestions from code review

Author: odow

docs/make.jl

@@ -1,6 +1,6 @@
 import Pkg
 Pkg.pkg"add Documenter#71e9f40"
-Pkg.pkg"add MathOptInterface#od/vector-optimization"
+Pkg.pkg"add MathOptInterface#master"
 import Documenter
 import Literate
 import Test

docs/src/manual/objective.md

@@ -180,7 +180,7 @@ In most cases, multi-objective optimization solvers will return multiple
 solutions, corresponding to points on the Pareto frontier. See [Multiple solutions](@ref)
 for information on how to query and work with multiple solutions.
 
-Note that you can must set a single objective sense, that is, you cannot have
+Note that you must set a single objective sense, that is, you cannot have
 both minimization and maximization objectives. Work around this limitation by
 choosing `Min` and negating any objectives you want to maximize:
 

test/runtests.jl

@@ -9,7 +9,7 @@
 #############################################################################
 
 import Pkg
-Pkg.pkg"add MathOptInterface#od/vector-optimization"
+Pkg.pkg"add MathOptInterface#master"
 
 import JuMP
 import Test

test/test_generate_and_solve.jl

@@ -566,7 +566,6 @@ function test_generate_solve_vector_objective()
     MOI.set(mock, MOI.ResultCount(), 1)
     MOI.set(mock, MOI.PrimalStatus(), MOI.FEASIBLE_POINT)
     MOI.set(mock, MOI.DualStatus(), MOI.NO_SOLUTION)
-    # MOI.set(mock, MOI.ObjectiveValue(), [0.0, 1.0])
     MOI.set(mock, MOI.ObjectiveBound(), [0.0, 1.0])
     MOI.set(mock, MOI.VariablePrimal(), optimizer_index(x), 0.0)
     MOI.set(mock, MOI.VariablePrimal(), optimizer_index(y), 1.0)