Slight re-formatting of utilities.jl.

src/utilities.jl

@@ -39,16 +39,19 @@ function mypickle(filename, obj)
 
 # Description: function computing the D matrix used for the renewable power plant siting application
 #
-# Inputs: A - matrix with entries between 0 and 1; rows correspond to time periods, columns correspond to locations; entries represent capacity factors
+# Inputs: A - matrix with entries between 0 and 1 representing capacity factors; rows correspond to time periods
+#         and columns correspond to locations
 #         demand - vector storing the electricity demand at each time period
-#         potential - vector storing the technical potential of each location (i.e., the maximum amount of capacity that may be deployed there)
+#         potential - vector storing the technical potential of each location (i.e., the maximum amount of capacity
+#         that may be deployed there)
 #         k - number of locations to select
 #         varsigma - share of the electricity demand that each location must supply in order to cover a time period
 #
-# Outputs: D - binary matrix indicating whether locations cover time periods (i.e., D_tl = 1 if location l covers time period t and 0 otherwise)
+# Outputs: D - binary matrix indicating which sets (columns) cover which elements (rows), that is, D_mn = 1 if set n covers element m
+#             and D_mn = 0 otherwise
 #
 
-function compute_D(A::Array{Float64, 2}, demand::Vector{Float64}, potential::Vector{Float64}, k::Int64, varsigma::Float64)::Array{Float64, 2}
+function compute_D(A::Array{Float64, 2}, demand::Vector{Float64}, potential::Vector{Float64}, k::Int64, varsigma::Float64)
 
     T::Int64, L::Int64 = size(A)
     D::Array{Float64, 2} = zeros(Float64, T, L)
@@ -68,7 +71,7 @@ function compute_D(A::Array{Float64, 2}, demand::Vector{Float64}, potential::Vec
     return D
 end
 
-function compute_D(A::Array{Float64, 2}, demand::Vector{Float64}, potential::Vector{Float64}, k::Float64, varsigma::Float64)::Array{Float64, 2}
+function compute_D(A::Array{Float64, 2}, demand::Vector{Float64}, potential::Vector{Float64}, k::Float64, varsigma::Float64)
 
     T::Int64, L::Int64 = size(A)
     D::Array{Float64, 2} = zeros(Float64, T, L)
@@ -92,7 +95,8 @@ end
 
 # Description: function computing the objective associated with a set of locations and coverage parameter
 #
-# Inputs: D - binary matrix indicating which sets (columns) cover which elements (rows), i.e., D_mn = 1 if set n covers element m and 0 otherwise
+# Inputs: D - binary matrix indicating which sets (columns) cover which elements (rows), that is, D_mn = 1 if set n covers element m
+#             and D_mn = 0 otherwise
 #         ind_incumbent - locations in the incumbent solution
 #         c - coverage parameter
 #
@@ -137,7 +141,8 @@ end
 
 # Description: function computing the objective gain achieved by selecting a (candidate) set
 #
-# Inputs: D - binary matrix indicating which sets (columns) cover which elements (rows), i.e., D_mn = 1 if set n covers element m and 0 otherwise
+# Inputs: D - binary matrix indicating which sets (columns) cover which elements (rows), that is, D_mn = 1 if set n covers element m
+#             and D_mn = 0 otherwise
 #         d - vector storing the contribution of all sets that were selected previously
 #         threshold - substitute for coverage parameter
 #         ind - index of candidate set