adding module based jl file

src/jl/main_heuristics_module.jl

+using PyCall
+
+include("optimisation_models.jl")
+include("MCP_heuristics.jl")
+
+module Siting_Heuristics
+
+# Simulated Annealing & Local Search algorithm
+function main_MIRSA(index_dict, deployment_dict, D, c, N, I, E, T_init, R, run)
+
+  index_dict = Dict([(convert(Int64, k), convert(Int64, index_dict[k])) for k in keys(index_dict)])
+  deployment_dict = Dict([(convert(Int64, k), convert(Int64, deployment_dict[k])) for k in keys(deployment_dict)])
+  D  = convert.(Float64, D)
+
+  c = convert(Float64, c)
+  N = convert(Int64, N)
+  I = convert(Int64, I)
+  E = convert(Int64, E)
+  T_init = convert(Float64, T_init)
+  R = convert(Int64, R)
+  run = string(run)
+
+  W, L = size(D)
+
+  P = maximum(values(index_dict))
+  n_partitions = [deployment_dict[i] for i in 1:P]
+
+  if run == "SALS"
+
+    x_sol, LB_sol, obj_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R), Array{Float64, 2}(undef, R, I)
+    x_init = solve_MILP_partitioning(D, c, n_partitions, index_dict, "Gurobi")
+
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r], obj_sol[r, :] = simulated_annealing_local_search_partition(D, c, n_partitions, N, I, E, x_init, T_init, index_dict)
+    end
+
+  elseif run == "SALSR"
+
+    x_sol, LB_sol, obj_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R), Array{Float64, 2}(undef, R, I)
+    x_init = zeros(Float64, L)
+    ind = collect(1:L)
+    x_ind = sample(ind, convert(Int64, deployment_dict[1]))
+    x_init[x_ind] .= 1.
+    n = convert(Float64, deployment_dict[1])
+
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r], obj_sol[r, :] = simulated_annealing_local_search(D, c, n, N, I, E, x_init, T_init)
+    end
+
+  else
+    println("No such run available.")
+    throw(ArgumentError)
+  end
+
+  return x_sol, LB_sol, obj_sol
+
+end
+
+# Random Search algorithm
+function main_RAND(deployment_dict, D, c, run)
+
+  deployment_dict = Dict([(convert(Int64, k), convert(Int64, deployment_dict[k])) for k in keys(deployment_dict)])
+  D  = convert.(Float64, D)
+  c = convert(Float64, c)
+
+  if run == "RS"
+
+    x_sol, LB_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R)
+    n = convert(Float64, deployment_dict[1])
+    runs = convert(Int64, I*E)
+
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r] = random_search(D, c, n, runs)
+    end
+
+  else
+    println("No such run available.")
+    throw(ArgumentError)
+  end
+
+  return x_sol, LB_sol
+
+end
+
+# Greedy algorithms
+function main_GRED(deployment_dict, D, c, run)
+
+  deployment_dict = Dict([(convert(Int64, k), convert(Int64, deployment_dict[k])) for k in keys(deployment_dict)])
+  D  = convert.(Float64, D)
+  c = convert(Float64, c)
+
+  if run == "RGH"
+    x_sol, LB_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R)
+    n = convert(Float64, deployment_dict[1])
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r] = randomised_greedy_heuristic(D, c, n)
+    end
+  elseif run == "CGA"
+    x_sol, LB_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R)
+    n = convert(Float64, deployment_dict[1])
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r] = classic_greedy_algorithm(D, c, n)
+    end
+  elif run == "SGA"
+    x_sol, LB_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R)
+    n = convert(Float64, deployment_dict[1])
+    eps = convert(Float64, 0.001)
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r] = stochastic_greedy_algorithm(D, c, n, eps)
+    end
+  else
+    println("No such run available.")
+    throw(ArgumentError)
+  end
+
+  return x_sol, LB_sol
+
+end
+
+#Local Search algorithm
+function main_LSEA(index_dict, deployment_dict, D, c, N, I, E, run)
+
+  index_dict = Dict([(convert(Int64, k), convert(Int64, index_dict[k])) for k in keys(index_dict)])
+  deployment_dict = Dict([(convert(Int64, k), convert(Int64, deployment_dict[k])) for k in keys(deployment_dict)])
+  D  = convert.(Float64, D)
+
+  c = convert(Float64, c)
+  N = convert(Int64, N)
+  I = convert(Int64, I)
+  E = convert(Int64, E)
+  T_init = convert(Float64, T_init)
+  R = convert(Int64, R)
+  run = string(run)
+
+  W, L = size(D)
+
+  P = maximum(values(index_dict))
+  n_partitions = [deployment_dict[i] for i in 1:P]
+
+  if run == "GLS"
+    x_sol, LB_sol, obj_sol = Array{Float64, 2}(undef, R, L), Array{Float64, 1}(undef, R), Array{Float64, 2}(undef, R, I)
+    x_init = solve_MILP_partitioning(D, c, n_partitions, index_dict, "Gurobi")
+    for r = 1:R
+      println("Run ", r, "/", R)
+      x_sol[r, :], LB_sol[r], obj_sol[r, :] = greedy_local_search_partition(D, c, n_partitions, N, I, E, x_init, index_dict)
+    end
+  else
+    println("No such run available.")
+    throw(ArgumentError)
+  end
+
+  return x_sol, LB_sol, obj_sol
+
+end
+
+end