RosettaCodeData/Task/Knapsack-problem-0-1/Crystal/knapsack-problem-0-1.crystal
2023-07-01 13:44:08 -04:00

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require "bit_array"
struct BitArray
def clone
BitArray.new(size).tap { |new| new.to_slice.copy_from (to_slice) }
end
end
record Item, name : String, weight : Int32, value : Int32
record Selection, mask : BitArray, cur_index : Int32, total_value : Int32
class Knapsack
@threshold_value = 0
@threshold_choice : Selection?
getter checked_nodes = 0
def knapsack_step(taken, items, remaining_weight)
if taken.total_value > @threshold_value
@threshold_value = taken.total_value
@threshold_choice = taken
end
candidate_index = items.index(taken.cur_index) { |item| item.weight <= remaining_weight }
return nil unless candidate_index
@checked_nodes += 1
candidate = items[candidate_index]
# candidate is a best of available items, so if we fill remaining value with it
# and still don't reach the threshold, the branch is wrong
return nil if taken.total_value + 1.0 * candidate.value / candidate.weight * remaining_weight < @threshold_value
# now recursively check both variants
mask = taken.mask.clone
mask[candidate_index] = true
knapsack_step Selection.new(mask, candidate_index + 1, taken.total_value + candidate.value), items, remaining_weight - candidate.weight
mask = taken.mask.clone
mask[candidate_index] = false
knapsack_step Selection.new(mask, candidate_index + 1, taken.total_value), items, remaining_weight
end
def select(items, max_weight)
@checked_variants = 0
# sort by descending relative value
list = items.sort_by { |item| -1.0 * item.value / item.weight }
# use heuristic of relative value as an initial estimate for branch&bounds
w = max_weight
heur_list = list.take_while { |item| w -= item.weight; w > 0 }
nothing = Selection.new(BitArray.new(items.size), 0, 0)
@threshold_value = heur_list.sum(&.value) - 1
@threshold_choice = nothing
knapsack_step(nothing, list, max_weight)
selected = @threshold_choice.not_nil!
result = [] of Item
selected.mask.each_with_index { |v, i| result << list[i] if v }
result
end
end
possible = [
Item.new("map", 9, 150),
Item.new("compass", 13, 35),
Item.new("water", 153, 200),
Item.new("sandwich", 50, 160),
Item.new("glucose", 15, 60),
Item.new("tin", 68, 45),
Item.new("banana", 27, 60),
Item.new("apple", 39, 40),
Item.new("cheese", 23, 30),
Item.new("beer", 52, 10),
Item.new("suntan cream", 11, 70),
Item.new("camera", 32, 30),
Item.new("T-shirt", 24, 15),
Item.new("trousers", 48, 10),
Item.new("umbrella", 73, 40),
Item.new("waterproof trousers", 42, 70),
Item.new("waterproof overclothes", 43, 75),
Item.new("note-case", 22, 80),
Item.new("sunglasses", 7, 20),
Item.new("towel", 18, 12),
Item.new("socks", 4, 50),
Item.new("book", 30, 10),
]
solver = Knapsack.new
used = solver.select(possible, 400)
puts "optimal choice: #{used.map(&.name)}"
puts "total weight #{used.sum(&.weight)}, total value #{used.sum(&.value)}"
puts "checked nodes: #{solver.checked_nodes}"