Fix set cover (#41)

* fix set cover

* Update test/models/SetCovering.jl

src/models/SetCovering.jl

@@ -7,7 +7,6 @@ Positional arguments
 -------------------------------
 * `sets` is a vector of vectors, a collection of subsets of universe , each set is associated with a weight specified in `weights`.
 * `weights` are associated with sets.
-
 """
 
 struct SetCovering{ET, WT<:Union{UnitWeight, Vector}} <: AbstractProblem
@@ -22,10 +21,7 @@ Base.:(==)(a::SetCovering, b::SetCovering) = a.sets == b.sets && a.weights == b.
 
 #variables interface
 variables(gp::SetCovering) = gp.sets
-num_variables(c::SetCovering) = length(c.sets)
-flavors(::Type{<:SetCovering}) = [0, 1] #whether the set is selected or not
-
-
+flavors(::Type{<:SetCovering}) = [0, 1] # whether the set is selected (1) or not (0)
 
 # weights interface
 parameters(c::SetCovering) = c.weights
@@ -41,33 +37,12 @@ sum of the weights of the sets that are selected. Config is a vector of boolean
 
 function evaluate(c::SetCovering, config)
     @assert length(config) == num_variables(c)
-    set_covering_energy(c.weights, config )
+    set_covering_energy(c.sets, c.weights, config )
 end
-set_covering_energy(weights::AbstractVector, config) = sum(weights[i]*config[i] for i=1:length(weights))
-
-"""
-    findbest(c::SetCovering) -> Vector
-
-Find the best configurations of the `c` using the `method`. We offer bruteforce search as the default method.
-
-"""
-
-function findbest(c::SetCovering, method="bruteforce")
-    best = nothing
-    best_energy = Inf 
-    for config in Iterators.product((fill([0,1],num_variables(c)))...)
-        if sum(config) == 0
-            continue
-        end
-        if is_set_covering(c,config)
-            energy = evaluate(c,config)
-            if energy < best_energy
-                best = config
-                best_energy = energy
-            end
-        end
-    end
-    return best
+function set_covering_energy(sets::AbstractVector, weights::AbstractVector, config)
+    @assert length(sets) == length(weights) == length(config)
+    !is_set_covering(SetCovering(sets, weights), config) && return typemax(eltype(weights))
+    return sum(weights[i] * config[i] for i=1:length(weights))
 end
 
 """
@@ -76,5 +51,6 @@ end
 Return true if `config` (a vector of boolean numbers as the mask of sets) is a set covering of `sets`.
 """
 function is_set_covering(c::SetCovering, config)
-    return reduce(union,c.sets)==reduce(union,c.sets[i] for i in 1:length(config) if config[i]==1)
+    @assert length(config) == num_variables(c)
+    return Set(vcat(c.sets...)) == Set(vcat([c.sets[i] for i in 1:length(config) if config[i]==1]...))
 end

test/models/SetCovering.jl

@@ -14,14 +14,15 @@ using ProblemReductions: SetCovering, variables, flavors, terms, evaluate, set_p
     @test set_parameters(c, [1, 2, 3]) == SetCovering([[1, 2], [2, 3], [2, 3, 4]], [1, 2, 3])
 
     # evaluate
-    @test evaluate(c, [0, 1, 1]) == 3
-    @test set_covering_energy([1, 1, 2], [0, 0, 1]) == 2
+    @test evaluate(c, [0, 1, 1]) == typemax(Int)
+    @test evaluate(c, [1, 0, 1]) == 3
+    @test set_covering_energy(c.sets, [1, 1, 2], [0, 0, 1]) == typemax(Int)
     @test is_set_covering(c,[1,0,1]) == true
     @test is_set_covering(c,[0,0,1]) == false
 
     # findbest
-    @test findbest(c) == (1,0,1)
-    @test findbest(c, "bruteforce") == (1,0,1)
+    @test findbest(c, BruteForce()) == [[1, 0, 1]]
+    @test findbest(c, BruteForce()) == [[1, 0, 1]]
     g = SetCovering([[1, 2], [1, 3, 4], [2, 3]], [1, 1, 2])
-    @test findbest(g) == (1,1,0)
+    @test findbest(g, BruteForce()) == [[1, 1, 0]]
 end