結果
| 問題 |
No.1301 Strange Graph Shortest Path
|
| コンテスト | |
| ユーザー |
👑 |
| 提出日時 | 2020-11-28 12:01:00 |
| 言語 | Lua (LuaJit 2.1.1734355927) |
| 結果 |
WA
|
| 実行時間 | - |
| コード長 | 7,592 bytes |
| コンパイル時間 | 361 ms |
| コンパイル使用メモリ | 6,948 KB |
| 実行使用メモリ | 89,412 KB |
| 最終ジャッジ日時 | 2024-09-12 22:19:57 |
| 合計ジャッジ時間 | 19,205 ms |
|
ジャッジサーバーID (参考情報) |
judge2 / judge5 |
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| ファイルパターン | 結果 |
|---|---|
| sample | AC * 2 |
| other | AC * 1 WA * 30 RE * 2 |
ソースコード
local mmi, mma = math.min, math.max
local MinCostFlow = {}
MinCostFlow.initialize = function(self, n, spos, tpos, inf)
self.n = n
self.spos, self.tpos = spos, tpos
self.inf = inf
-- edge_dst[src][i] := dst
self.edge_dst = {}
-- edge_cost[src][i] := cost from src to edge_dst[src][i]
self.edge_cost = {}
-- edge_cap[src][i] := capacity from src to edge_dst[src][i]
self.edge_cap = {}
-- initial capacity. corresponding to edge_cap
self.edge_initialcap = {}
-- edge_dst_invedge_idx[src][i] := "j" where edge_dst[dst][j] == src
-- in this case, edge_dst_invedge_idx[dst][j] should be "i".
self.edge_dst_invedge_idx = {}
-- len[v] := length from spos. len[spos] := 0
self.len = {}
-- sub_graph_flag[v] := temporal flag to restore shortest path
self.sub_graph_flag = {}
-- sub_graph_v[i] := list of vertexes that are contained in the sub-graph. from tpos to spos.
self.sub_graph_v = {}
-- sub_graph_edgeidx[i] := edge index from sub_graph_v[i + 1] to sub_graph_v[i]
self.sub_graph_edgeidx = {}
-- sub_graph_size := the size of sub_graph_v.
-- may not equal to #sub_graph_v (because not cleared).
self.sub_graph_size = 0
for i = 1, n do
self.edge_dst[i] = {}
self.edge_cost[i] = {}
self.edge_cap[i] = {}
self.edge_initialcap[i] = {}
self.edge_dst_invedge_idx[i] = {}
self.len[i] = 0
self.sub_graph_flag[i] = false
end
end
MinCostFlow.addEdge = function(self, src, dst, cost, cap)
table.insert(self.edge_dst[src], dst)
table.insert(self.edge_cost[src], cost)
table.insert(self.edge_cap[src], cap)
table.insert(self.edge_initialcap[src], cap)
table.insert(self.edge_dst_invedge_idx[src], 1 + #self.edge_dst[dst])
table.insert(self.edge_dst[dst], src)
table.insert(self.edge_cost[dst], -cost)
table.insert(self.edge_cap[dst], 0)--invcap
table.insert(self.edge_initialcap[dst], 0)--invcap
table.insert(self.edge_dst_invedge_idx[dst], #self.edge_dst[src])
end
MinCostFlow.invwalk_recursive = function(self, invsrc)
if invsrc == self.spos then return true end
local edge_cap, edge_cost = self.edge_cap, self.edge_cost
local len = self.len
local sub_graph_flag = self.sub_graph_flag
local sub_graph_v = self.sub_graph_v
local sub_graph_edgeidx = self.sub_graph_edgeidx
local eddsrc = self.edge_dst[invsrc]
local eddiisrc = self.edge_dst_invedge_idx[invsrc]
for i = 1, #eddsrc do
local invdst = eddsrc[i]
local j = eddiisrc[i]
if 0 < edge_cap[invdst][j]
and len[invdst] + edge_cost[invdst][j] == len[invsrc]
and not sub_graph_flag[invdst] then
self.sub_graph_size = self.sub_graph_size + 1
sub_graph_v[self.sub_graph_size] = invdst
sub_graph_edgeidx[self.sub_graph_size - 1] = j
sub_graph_flag[invdst] = true
if self:invwalk_recursive(invdst) then
return true
else
self.sub_graph_size = self.sub_graph_size - 1
end
end
end
return false
end
MinCostFlow.walkDK = function(self)
-- Dijkstra-like walk
local edge_dst, edge_cost, edge_cap = self.edge_dst, self.edge_cost, self.edge_cap
local len = self.len
local tasklim = self.n
if not self.taskstate then
self.taskstate = {}
self.tasks = {}
for i = 1, tasklim do self.taskstate[i] = false end
end
local taskstate = self.taskstate
local tasks = self.tasks
local tasknum, done = 0, 0
local function addtask(idx)
if not taskstate[idx] and idx ~= self.tpos then
taskstate[idx] = true
tasknum = tasknum + 1
local taskidx = tasknum % tasklim
if taskidx == 0 then taskidx = tasklim end
tasks[taskidx] = idx
end
end
local function walk(src, dst, cost)
if len[src] + cost < len[dst] then
len[dst] = len[src] + cost
addtask(dst)
end
end
addtask(self.spos)
while done < tasknum do
done = done + 1
local taskidx = done % tasklim
if taskidx == 0 then taskidx = tasklim end
local idx = tasks[taskidx]
taskstate[idx] = false
local eddst, edcap, edcost = edge_dst[idx], edge_cap[idx], edge_cost[idx]
for i = 1, #eddst do
if 0 < edcap[i] then
walk(idx, eddst[i], edcost[i])
end
end
end
end
MinCostFlow.walkBF = function(self)
--Bellman-Ford walk
local edge_dst, edge_cost, edge_cap = self.edge_dst, self.edge_cost, self.edge_cap
local len = self.len
local n = self.n
if not self.updated1 then
self.updated1 = {}
self.updated2 = {}
end
local updated1, updated2 = self.updated1, self.updated2
for i = 1, n do
updated1[i] = false
end
updated1[self.spos] = true
len[self.spos] = 0
for irp = 1, n do
local updsrc = irp % 2 == 1 and updated1 or updated2
local upddst = irp % 2 == 1 and updated2 or updated1
for i = 1, n do
upddst[i] = false
end
local alldone = true
for src = 1, n do
if updsrc[src] then
local eddst, edcap, edcost = edge_dst[src], edge_cap[src], edge_cost[src]
for i = 1, #eddst do
if 0 < edcap[i] then
local dst = eddst[i]
local cost = edcost[i]
if len[src] + cost < len[dst] then
len[dst] = len[src] + cost
upddst[dst] = true
alldone = false
end
end
end
end
end
if alldone then break end
end
end
MinCostFlow.makeSubGraph = function(self)
local inf = self.inf
local len = self.len
local n = self.n
local edge_dst, edge_cap = self.edge_dst, self.edge_cap
local edge_dst_invedge_idx = self.edge_dst_invedge_idx
local edge_cost = self.edge_cost
local sub_graph_v = self.sub_graph_v
local sub_graph_edgeidx = self.sub_graph_edgeidx
local sub_graph_flag = self.sub_graph_flag
for i = 1, n do
len[i] = inf
sub_graph_flag[i] = false
end
len[self.spos] = 0
-- Bellman-Ford is good, but Dijkstra-like is very fast in some case
self:walkDK()
-- self:walkBF()
self.sub_graph_size = 0
if inf <= len[self.tpos] then
return 0
end
-- restore route (from tpos to spos)
self.sub_graph_size = 1
sub_graph_v[1] = self.tpos
self:invwalk_recursive(self.tpos)
local min_capacity = inf
for i = self.sub_graph_size, 2, -1 do
local src = sub_graph_v[i]
local j = sub_graph_edgeidx[i - 1]
min_capacity = mmi(min_capacity, edge_cap[src][j])
end
return min_capacity
end
MinCostFlow.flow = function(self, capacity)
local edge_dst, edge_cap = self.edge_dst, self.edge_cap
local edge_dst_invedge_idx = self.edge_dst_invedge_idx
local sub_graph_v = self.sub_graph_v
local sub_graph_edgeidx = self.sub_graph_edgeidx
for i = self.sub_graph_size, 2, -1 do
local src = sub_graph_v[i]
local dst = sub_graph_v[i - 1]
local j = sub_graph_edgeidx[i - 1]
edge_cap[src][j] = edge_cap[src][j] - capacity
local k = edge_dst_invedge_idx[src][j]
edge_cap[dst][k] = edge_cap[dst][k] + capacity
end
end
MinCostFlow.getMinCostFlow = function(self, amount, invalid)
local ret = 0
local cap = self:makeSubGraph()
while 0 < cap do
cap = mmi(amount, cap)
ret = ret + self.len[self.tpos] * cap
self:flow(cap)
amount = amount - cap
if 0 < amount then
cap = self:makeSubGraph()
else
break
end
end
if 0 < amount then return invalid end
return ret
end
local mcf = MinCostFlow
local n = io.read("*n")
local m = io.read("*n")
mcf:initialize(n, 1, n, 1000000007)
for i = 1, m do
local u, v, c, d = io.read("*n", "*n", "*n", "*n")
mcf:addEdge(u, v, c, 1)
mcf:addEdge(u, v, d, 2)
mcf:addEdge(v, u, c, 1)
mcf:addEdge(v, u, d, 2)
end
print(mcf:getMinCostFlow(2))