Modularize LearningSolver into components; implement branch-priority

miplearn/scripts/branchpriority.jl

@@ -0,0 +1,67 @@
+import Base.Threads.@threads
+using TinyBnB, CPLEXW, Printf
+
+instance_name = ARGS[1]
+output_filename = ARGS[2]
+
+mip = open_mip(instance_name)
+n_vars = CPXgetnumcols(mip.cplex_env[1], mip.cplex_lp[1])
+
+pseudocost_count_up = [0 for i in 1:n_vars]
+pseudocost_count_down = [0 for i in 1:n_vars]
+pseudocost_sum_up = [0. for i in 1:n_vars]
+pseudocost_sum_down = [0. for i in 1:n_vars]
+
+function full_strong_branching_track(node::Node, progress::Progress)::TinyBnB.Variable
+    N = length(node.fractional_variables)
+    scores = Array{Float64}(undef, N)
+    rates_up = Array{Float64}(undef, N) 
+    rates_down = Array{Float64}(undef, N)
+    
+    @threads for v in 1:N
+        fix_vars!(node.mip, node.branch_variables, node.branch_values)
+        obj_up, obj_down = TinyBnB.probe(node.mip, node.fractional_variables[v])
+        unfix_vars!(node.mip, node.branch_variables)
+        delta_up  = obj_up - node.obj
+        delta_down = obj_down - node.obj
+        frac_up = ceil(node.fractional_values[v]) - node.fractional_values[v]
+        frac_down = node.fractional_values[v] - floor(node.fractional_values[v])
+        rates_up[v] = delta_up / frac_up
+        rates_down[v] = delta_down / frac_down
+        scores[v] = delta_up * delta_down
+    end
+
+    max_score, max_offset = findmax(scores)
+    selected_var = node.fractional_variables[max_offset]
+    
+    if rates_up[max_offset] < 1e6
+        pseudocost_count_up[selected_var.index] += 1
+        pseudocost_sum_up[selected_var.index] += rates_up[max_offset]
+    end
+    
+    if rates_down[max_offset] < 1e6
+        pseudocost_count_down[selected_var.index] += 1
+        pseudocost_sum_down[selected_var.index] += rates_down[max_offset]
+    end
+    
+    return selected_var
+end
+
+branch_and_bound(mip,
+                 node_limit = 1000,
+                 branch_rule = full_strong_branching_track,
+                 node_rule = best_bound,
+                 print_interval = 1)
+
+priority = [(pseudocost_count_up[v] == 0 || pseudocost_count_down[v] == 0) ? 0 :
+              (pseudocost_sum_up[v] / pseudocost_count_up[v]) *
+              (pseudocost_sum_down[v] / pseudocost_count_down[v])
+             for v in 1:n_vars];
+
+open(output_filename, "w") do file
+    for v in 1:n_vars
+        v == 1 || write(file, ",")
+        write(file, @sprintf("%.0f", priority[v]))
+    end
+    write(file, "\n")
+end