#!/usr/local/bin/pypy # python 想定解 O(NK)本の辺を張り,下駄をはかせる # zkou さん (@meander_uts1) のライブラリを使用(https://atcoder.jp/contests/practice2/submissions/18032049Ω) import heapq class mcf_graph: def __init__(self, n): self.n = n self.pos = [] self.g = [[] for _ in range(n)] def add_edge(self, from_, to, cap, cost): # assert 0 <= from_ < self.n # assert 0 <= to < self.n m = len(self.pos) self.pos.append((from_, len(self.g[from_]))) self.g[from_].append(self.__class__._edge(to, len(self.g[to]), cap, cost)) self.g[to].append(self.__class__._edge(from_, len(self.g[from_]) - 1, 0, -cost)) return m class edge: def __init__(self, from_, to, cap, flow, cost): self.from_ = from_ self.to = to self.cap = cap self.flow = flow self.cost = cost def get_edge(self, i): _e = self.g[self.pos[i][0]][self.pos[i][1]] _re = self.g[_e.to][_e.rev] return self.__class__.edge(self.pos[i][0], _e.to, _e.cap + _re.cap, _re.cap, _e.cost) def edges(self): ret = [] for i in range(len(self.pos)): _e = self.g[self.pos[i][0]][self.pos[i][1]] _re = self.g[_e.to][_e.rev] ret.append(self.__class__.edge(self.pos[i][0], _e.to, _e.cap + _re.cap, _re.cap, _e.cost)) return ret def _dual_ref(self, s, t): self.dist = [float('inf')] * self.n self.pv = [-1] * self.n self.pe = [-1] * self.n self.vis = [False] * self.n que = [(0, s)] self.dist[s] = 0 while que: _, v = heapq.heappop(que) if self.vis[v]: continue self.vis[v] = True if v == t: break for i in range(len(self.g[v])): e = self.g[v][i] if self.vis[e.to] or e.cap == 0: continue cost = e.cost - self.dual[e.to] + self.dual[v] if self.dist[e.to] > self.dist[v] + cost: self.dist[e.to] = self.dist[v] + cost self.pv[e.to] = v self.pe[e.to] = i heapq.heappush(que, (self.dist[e.to], e.to)) if not self.vis[t]: return False for v in range(self.n): if not self.vis[v]: continue self.dual[v] -= self.dist[t] - self.dist[v] return True def slope(self, s, t, flow_limit=float('inf')): # assert 0 <= s < self.n # assert 0 <= t < self.n # assert s != t self.dual = [0] * self.n self.dist = [float('inf')] * self.n self.pv = [-1] * self.n self.pe = [-1] * self.n self.vis = [False] * self.n flow = 0 cost = 0 prev_cost = -1 result = [(flow, cost)] while flow < flow_limit: if not self._dual_ref(s, t): break c = flow_limit - flow v = t while v != s: c = min(c, self.g[self.pv[v]][self.pe[v]].cap) v = self.pv[v] v = t while v != s: e = self.g[self.pv[v]][self.pe[v]] e.cap -= c self.g[v][e.rev].cap += c v = self.pv[v] d = -self.dual[s] flow += c cost += c * d if prev_cost == d: result.pop() result.append((flow, cost)) prev_cost = cost return result def flow(self, s, t, flow_limit=float('inf')): return self.slope(s, t, flow_limit)[-1] class _edge: def __init__(self, to, rev, cap, cost): self.to = to self.rev = rev self.cap = cap self.cost = cost import sys readline = sys.stdin.readline write = sys.stdout.write if __name__ == '__main__': BIG = 400 N, K = map(int, readline().split()) A = list(map(int, readline().split())) B = list(map(int, readline().split())) P = [] for i in range(N): P.append(list(map(int, readline().split()))) mcf = mcf_graph(2*N+2) s = 2*N t = s+1 for i in range(N): mcf.add_edge(s, i, A[i], 0) S = 0 for i in range(N): for j in range(N): S += P[i][j] * P[i][j] for x in range(A[i]): mcf.add_edge(i, N+j, 1, 2*(x-P[i][j])+1+BIG) for i in range(N): mcf.add_edge(N+i, t, B[i], 0) print(mcf.flow(s, t, K)[1] + S - K*BIG)