結果
| 問題 | No.5007 Steiner Space Travel |
| ユーザー |
 fujikawahiroaki
|
| 提出日時 | 2023-04-30 09:56:50 |
| 言語 | Crystal (1.11.2) |
| 結果 |
AC
|
| 実行時間 | 9 ms / 1,000 ms |
| コード長 | 12,798 bytes |
| コンパイル時間 | 27,000 ms |
| コンパイル使用メモリ | 269,088 KB |
| 実行使用メモリ | 5,060 KB |
| スコア | 6,034,094 |
| 最終ジャッジ日時 | 2023-04-30 09:57:56 |
| 合計ジャッジ時間 | 28,085 ms |
|
ジャッジサーバーID （参考情報） |
judge17 / judge11 |
| 純コード判定しない問題か言語 |
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テストケース
テストケース表示| 入力 | 結果 | 実行時間 実行使用メモリ |
|---|---|---|
| testcase_00 | AC | 8 ms
4,900 KB |
| testcase_01 | AC | 9 ms
4,936 KB |
| testcase_02 | AC | 9 ms
4,988 KB |
| testcase_03 | AC | 9 ms
4,924 KB |
| testcase_04 | AC | 9 ms
4,892 KB |
| testcase_05 | AC | 9 ms
4,924 KB |
| testcase_06 | AC | 9 ms
4,892 KB |
| testcase_07 | AC | 9 ms
4,944 KB |
| testcase_08 | AC | 9 ms
4,844 KB |
| testcase_09 | AC | 9 ms
4,932 KB |
| testcase_10 | AC | 9 ms
4,972 KB |
| testcase_11 | AC | 9 ms
4,980 KB |
| testcase_12 | AC | 9 ms
4,960 KB |
| testcase_13 | AC | 8 ms
4,992 KB |
| testcase_14 | AC | 9 ms
4,984 KB |
| testcase_15 | AC | 8 ms
4,952 KB |
| testcase_16 | AC | 8 ms
4,860 KB |
| testcase_17 | AC | 8 ms
4,940 KB |
| testcase_18 | AC | 9 ms
4,988 KB |
| testcase_19 | AC | 9 ms
5,016 KB |
| testcase_20 | AC | 9 ms
4,916 KB |
| testcase_21 | AC | 8 ms
4,992 KB |
| testcase_22 | AC | 9 ms
4,904 KB |
| testcase_23 | AC | 9 ms
4,892 KB |
| testcase_24 | AC | 8 ms
4,944 KB |
| testcase_25 | AC | 9 ms
5,060 KB |
| testcase_26 | AC | 9 ms
4,996 KB |
| testcase_27 | AC | 9 ms
4,968 KB |
| testcase_28 | AC | 8 ms
4,964 KB |
| testcase_29 | AC | 9 ms
4,952 KB |
ソースコード
# 定数
NUM_PLANETS = 100i64
NUM_STATIONS = 8i64
SUM_POINTS = NUM_PLANETS + NUM_STATIONS # 総地点数
PLANET_MOVE_COST = 5i64 # 問題文ではα
COORD_MIN = 0i64 # 座標の下限値
COORD_MAX = 1000i64 # 座標の上限値
TYPE_PLANET = 1i64 # 経由地が惑星
TYPE_STATION = 2i64 # 経由地が宇宙ステーション
INF = 10i64 ** 18 # 距離の初期値など、あり得ない大きな数に使う
TIME_LIMIT = 0.95 # 時間制限
# 入力受け取り
# 惑星の数と宇宙ステーションの数、問題文のNとMに対応
start_time = Time.utc
n, m = read_line.split.map(&.to_i64)
# 各惑星の座標
coord_planets = Hash(Int64, Tuple(Int64, Int64)).new
n.times do |i|
a, b = read_line.split.map(&.to_i64)
coord_planets[i] = {a, b}
end
cluster_of_planet, centers, clusters = make_cluster(coord_planets)
coord_stations = Hash(Int64, Tuple(Int64, Int64)).new
m.times do |i|
coord_stations[NUM_PLANETS + i] = centers[i]
end
STDERR.puts coord_stations
dist_table = make_dist_table(coord_planets, coord_stations)
# 解法を実行し出力
ans_route = solve(coord_planets, coord_stations, cluster_of_planet, clusters, dist_table, start_time)
coord_stations.each_value do |xy|
x, y = xy
puts "#{x} #{y}"
end
puts ans_route.size
ans_route.each do |point|
type = get_point_type(point)
point += 1
point -= NUM_PLANETS if type == TYPE_STATION
puts "#{type} #{point}"
end
# ソルバ
def solve(coord_planets, coord_stations, cluster_of_planet, clusters, dist_table, start_time)
route = cluster_route(coord_planets, coord_stations, cluster_of_planet, clusters, dist_table)
# route = greedy_route(coord_planets, coord_stations, dist_table)
score, opt2_route = opt2(coord_planets, coord_stations, dist_table, route)
# ans_route = [] of Int64
# route_size = opt2_route.size.to_i64 // 8
# station_number = NUM_PLANETS
# station_change_cnt = 0i64
# opt2_route.each_with_index do |point, i|
# ans_route << point
# if i % route_size == 0 && station_change_cnt < 8
# coord_stations[station_number] = coord_planets[point]
# ans_route << station_number
# station_number += 1
# station_change_cnt += 1
# end
# end
# ans_route
opt2_route
end
# 2点間の移動に要するエネルギーを計算
def calc_cost(pos1 : Tuple(Int64, Int64), pos2 : Tuple(Int64, Int64), type1 : Int64, type2 : Int64) : Int64
x1, y1 = pos1
x2, y2 = pos2
euc_dist = ((Math.sqrt((x1 - x2) ** 2 + (y1 - y2) ** 2)) ** 2).to_i64
if type1 == TYPE_PLANET && type2 == TYPE_PLANET
return (PLANET_MOVE_COST ** 2) * euc_dist
elsif type1 == TYPE_STATION && type2 == TYPE_STATION
return euc_dist
else
return PLANET_MOVE_COST * euc_dist
end
end
# 指定した地点が惑星か宇宙ステーションかを判別し、該当する判別番号を返す
# ただし地点番号は問題文と異なり0-indexedであることに注意せよ
def get_point_type(point : Int64)
point < NUM_PLANETS ? TYPE_PLANET : TYPE_STATION
end
# 各経由地間の距離を計算し、二次元配列にまとめて返す
def make_dist_table(coord_planets : Hash(Int64, Tuple(Int64, Int64)), coord_stations : Hash(Int64, Tuple(Int64, Int64))) : Array(Array(Int64))
table_size = NUM_PLANETS + NUM_STATIONS
dist_table = Array.new(table_size) { [0i64] * table_size }
table_size.times do |i|
table_size.times do |j|
pos1 = i < NUM_PLANETS ? coord_planets[i] : coord_stations[i]
pos2 = j < NUM_PLANETS ? coord_planets[j] : coord_stations[j]
type1 = get_point_type(i)
type2 = get_point_type(j)
dist_table[i][j] = calc_cost(pos1, pos2, type1, type2)
end
end
# ワーシャルフロイド法
SUM_POINTS.times do |k|
SUM_POINTS.times do |i|
SUM_POINTS.times do |j|
d = dist_table[i][k] + dist_table[k][j]
dist_table[i][j] = dist_table[i][j] < d ? dist_table[i][j] : d
end
end
end
dist_table
end
# ダイクストラ法によって経由地iから経由地jへの最短経路を復元
def dijkstra(i : Int64, j : Int64, coord_planets : Hash(Int64, Tuple(Int64, Int64)), coord_stations : Hash(Int64, Tuple(Int64, Int64)))
dists = [INF] * SUM_POINTS
prev_points = [-1i64] * SUM_POINTS
q = AtCoder::PriorityQueue(Tuple(Int64, Int64)).new { |a, b| a >= b }
dists[i] = 0i64
q << {0i64, i}
until q.empty?
dist, point = q.pop.not_nil!
next if dist > dists[point]
SUM_POINTS.times do |next_point|
type1 = get_point_type(point)
type2 = get_point_type(next_point)
pos1 = type1 == TYPE_PLANET ? coord_planets[point] : coord_stations[point]
pos2 = type2 == TYPE_PLANET ? coord_planets[next_point] : coord_stations[next_point]
next_dist = dist + calc_cost(pos1, pos2, type1, type2)
if next_dist < dists[next_point]
prev_points[next_point] = point
dists[next_point] = next_dist
q << {next_dist, next_point}
end
end
end
point = j
path = [] of Int64
while point != i
path << point
point = prev_points[point]
end
path.reverse!
end
# 距離の近い惑星同士のクラスタを生成
def make_cluster(coord_planets)
# k-means法もどき
cluster_of_planet = Hash(Int64, Int64).new
NUM_PLANETS.times do |planet|
cluster_of_planet[planet] = Random.rand(NUM_STATIONS)
end
clusters = Array.new(NUM_STATIONS) { [] of Int64 }
cluster_of_planet.each do |k, v|
clusters[v] << k
end
centers = [] of Tuple(Int64, Int64)
NUM_STATIONS.times do
centers << coord_planets.sample[1]
end
finish = false
until finish
prev_centers = centers
new_clusters = Array.new(NUM_STATIONS) { [] of Int64 }
old_cluster_of_planet = cluster_of_planet.clone
NUM_PLANETS.times do |planet|
planet_pos = coord_planets[planet]
dists = centers.map_with_index { |center, cluster_number|
x2, y2 = center
{calc_cost(planet_pos, center, TYPE_PLANET, TYPE_STATION), cluster_number}
}.sort!
dists.each do |dist_and_cluster_number|
dist, cluster_number = dist_and_cluster_number
new_clusters[cluster_number] << planet
cluster_of_planet[planet] = cluster_number
break
end
end
if new_clusters.includes?([] of Int64)
return {old_cluster_of_planet, centers, clusters}
end
clusters = new_clusters
centers = [] of Tuple(Int64, Int64)
clusters.each do |cluster|
centers << calc_center_of_cluster(cluster, coord_planets)
end
finish = true if centers == prev_centers
end
STDERR.puts clusters
STDERR.puts cluster_of_planet
{cluster_of_planet, centers, clusters}
end
# クラスタの中心座標を求める
def calc_center_of_cluster(cluster, coord_planets)
center = [0.0, 0.0]
cluster_size = cluster.size
STDERR.puts cluster_size
cluster.each do |point|
center[0] += coord_planets[point][0]
center[1] += coord_planets[point][1]
end
center[0] /= cluster_size unless center[0] == 0
center[1] /= cluster_size unless center[0] == 0
{center[0].to_i64, center[1].to_i64}
end
# 各宇宙ステーションを一周しながら周辺の惑星を訪問し初期解を作る
def cluster_route(coord_planets, coord_stations, cluster_of_planet, clusters, dist_table)
current_station = cluster_of_planet[0]
visited = [false] * NUM_STATIONS
visited[current_station] = true
route = [0i64]
(NUM_STATIONS).times do
nearest_dist = INF
nearest_station = -1i64
NUM_STATIONS.times do |next_station|
next if visited[next_station]
if dist_table[current_station + NUM_PLANETS][next_station + NUM_PLANETS] < nearest_dist
nearest_dist = dist_table[current_station + NUM_PLANETS][next_station + NUM_PLANETS]
nearest_station = next_station
end
end
route << current_station + NUM_PLANETS
clusters[current_station].each do |planet|
route << planet if planet != 0
route << current_station + NUM_PLANETS
end
route << current_station + NUM_PLANETS
current_station = nearest_station
visited[current_station] = true
end
route << (cluster_of_planet[0] + NUM_PLANETS)
route << 0i64
STDERR.puts route
route
end
# 単純な貪欲法で初期解を作る
def greedy_route(coord_planets : Hash(Int64, Tuple(Int64, Int64)), coord_stations : Hash(Int64, Tuple(Int64, Int64)), dist_table)
point = 0i64
visited = [false] * SUM_POINTS
visited[0] = true
route = [0i64]
(SUM_POINTS - 1).times do |i|
nearest_dist = INF
nearest_point = -1i64
SUM_POINTS.times do |next_point|
next if visited[next_point]
if dist_table[point][next_point] < nearest_dist
nearest_dist = dist_table[point][next_point]
nearest_point = next_point
end
end
path = dijkstra(point, nearest_point, coord_planets, coord_stations)
route += path
point = nearest_point
visited[point] = true
end
route += dijkstra(point, 0i64, coord_planets, coord_stations)
STDERR.puts route
route
end
# 2-opt法で経路を改善
def opt2(coord_planets : Hash(Int64, Tuple(Int64, Int64)), coord_stations : Hash(Int64, Tuple(Int64, Int64)), dist_table, route_arg)
total_dist = 0i64
route = route_arg.clone
loop do
cnt = 0i64
(SUM_POINTS - 2).times do |i|
i1 = i + 1
(i + 2).upto(SUM_POINTS - 1) do |j|
j1 = j == SUM_POINTS - 1 ? 0i64 : j + 1
if i != 0 || j1 != 0
l1 = dist_table[route[i]][route[i1]]
l2 = dist_table[route[j]][route[j1]]
l3 = dist_table[route[i]][route[j]]
l4 = dist_table[route[i1]][route[j1]]
if l1 + l2 > l3 + l4
route[i1..j] = route[i1..j].reverse!
cnt += 1
end
end
end
end
total_dist += cnt
break if cnt == 0
end
{total_dist, route}
end
# ac-library.cr by hakatashi https://github.com/google/ac-library.cr
#
# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
module AtCoder
# Implements standard priority queue like [std::priority_queue](https://en.cppreference.com/w/cpp/container/priority_queue).
#
# ```
# q = AtCoder::PriorityQueue(Int64).new
# q << 1_i64
# q << 3_i64
# q << 2_i64
# q.pop # => 3
# q.pop # => 2
# q.pop # => 1
# ```
class PriorityQueue(T)
getter heap : Array(T)
def initialize
initialize { |a, b| a <= b }
end
# Initializes queue with the custom comperator.
#
# If the second argument `b` should be popped earlier than
# the first argument `a`, return `true`. Else, return `false`.
#
# ```
# q = AtCoder::PriorityQueue(Int64).new { |a, b| a >= b }
# q << 1_i64
# q << 3_i64
# q << 2_i64
# q.pop # => 1
# q.pop # => 2
# q.pop # => 3
# ```
def initialize(&block : T, T -> Bool)
@heap = Array(T).new
@compare_proc = block
end
# Pushes value into the queue.
def push(v : T)
@heap << v
index = @heap.size - 1
while index != 0
parent = (index - 1) // 2
if @compare_proc.call(@heap[index], @heap[parent])
break
end
@heap[parent], @heap[index] = @heap[index], @heap[parent]
index = parent
end
end
# Alias of `push`
def <<(v : T)
push(v)
end
# Pops value from the queue.
def pop
if @heap.size == 0
return nil
end
if @heap.size == 1
return @heap.pop
end
ret = @heap.first
@heap[0] = @heap.pop
index = 0
while index * 2 + 1 < @heap.size
child = if index * 2 + 2 < @heap.size && !@compare_proc.call(@heap[index * 2 + 2], @heap[index * 2 + 1])
index * 2 + 2
else
index * 2 + 1
end
if @compare_proc.call(@heap[child], @heap[index])
break
end
@heap[child], @heap[index] = @heap[index], @heap[child]
index = child
end
ret
end
# Returns `true` if the queue is empty.
delegate :empty?, to: @heap
# Returns size of the queue.
delegate :size, to: @heap
end
end