📅  最后修改于: 2023-12-03 14:38:49.671000             🧑  作者: Mango
2-可满足性(2-SAT)问题是在布尔逻辑中的一个经典计算问题。给定一组布尔变量和一组约束条件,我们的目标是找到一个变量的赋值方案,使得所有约束条件都满足。
2-SAT问题可以转化为有向图中的强连通分量(SCC)问题,并使用图论算法来解决。具体步骤如下:
代码示例:
import numpy as np
class TwoSAT:
def __init__(self, num_vars):
self.num_vars = num_vars
self.graph = [[] for _ in range(2 * num_vars)]
def add_clause(self, a, b):
self.graph[self.negate_literal(a)].append(b)
self.graph[self.negate_literal(b)].append(a)
def negate_literal(self, lit):
return (2 * lit + self.num_vars) % (2 * self.num_vars)
def tarjan_scc(self):
index_counter = [0]
stack = []
lowlink = [0] * (2 * self.num_vars)
index = [-1] * (2 * self.num_vars)
on_stack = [False] * (2 * self.num_vars)
sccs = []
def strongconnect(v):
index[v] = index_counter[0]
lowlink[v] = index_counter[0]
index_counter[0] += 1
stack.append(v)
on_stack[v] = True
for w in self.graph[v]:
if index[w] == -1:
strongconnect(w)
lowlink[v] = min(lowlink[v], lowlink[w])
elif on_stack[w]:
lowlink[v] = min(lowlink[v], index[w])
if lowlink[v] == index[v]:
scc = []
while True:
w = stack.pop()
on_stack[w] = False
scc.append(w)
if w == v:
break
sccs.append(scc)
for v in range(2 * self.num_vars):
if index[v] == -1:
strongconnect(v)
return sccs
def is_satisfiable(self):
sccs = self.tarjan_scc()
for scc in sccs:
vars_in_scc = [literal // 2 for literal in scc]
for var in vars_in_scc:
if self.negate_literal(var) in scc:
return False
return True
# 使用示例:
solver = TwoSAT(2) # 创建一个有两个变量的2-SAT求解器
solver.add_clause(0, 1) # 添加约束条件
if solver.is_satisfiable():
print("可满足")
else:
print("不可满足")
2-SAT问题是一个经典的布尔逻辑计算问题,可以通过构建有向图和运行强连通分量算法来解决。上述代码提供了一个简单的2-SAT求解器示例,你可以根据自己的需求扩展和优化它。