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[[图论]]中,'''割'''(cut)是将图的[[顶点 (图论)|顶点]]分为两[[不交集|不交子集]]的[[集合划分|划分]]。<ref name="networkx.algorithms.cuts.cut_size">{{cite web | title=NetworkX 2.6.2 documentation | website=networkx.algorithms.cuts.cut_size | url=https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html#networkx.algorithms.cuts.cut_size | access-date=2021-12-10 | quote=A cut is a partition of the nodes of a graph into two sets. The cut size is the sum of the weights of the edges “between” the two sets of nodes. | archive-date=2021-11-18 | archive-url=https://web.archive.org/web/20211118095812/https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html#networkx.algorithms.cuts.cut_size | url-status=live }}</ref>割确定了'''割集''',是两端分别在两子集中的边集,称这些边'''跨过'''(cross)了割。[[连通图]]中,割集唯一确定一个割,识别割有时是通过割集,而非顶点划分。 [[网络流]]中,'''s–t割'''指使得源与汇不在同一子集的割,其割集只含源一侧到汇一侧的边。s-t割的容量(capacity)定义为割集中所有边的容量和。 ==定义== '''割'''<math>C=(S,\ T)</math>是将图<math>G=(V,\ E)</math>的顶点''V''分为两子集''S''、''T''的划分。 割<math>C=(S,\ T)</math>的'''割集'''是一端点位于''S''、另一端点位于''T''的边的集合<math>\{(u,\ v)\in E|u\in S,\ v\in T\}</math>。 令''s''、''t''是图''G''的两顶点,则'''{{mvar|s–t}}割'''是使得''s''属于''S''、''t''属于''T''的割。 在无权无向图中,割的大小(size)或权(weight)是跨过割的边数。加权图中,割的'''值'''(value)或'''权'''(weight)是跨过割的边的权重之和。 '''键'''(bond)是[[真子集]]中没有其他割集的割集。 ==最小割== [[File:Min-cut.svg|thumb|right|一个最小割。]] {{main|最小割}} 最小割的大小或权不大于其他割。右图展示了最小割,其大小为2,且没有大小为1的割,因为这张图没有[[桥 (图论)|桥]]。 [[最大流最小割定理]]指出,最大[[网络流]]等于分割了源汇的最小割的割边权重之和。有一些[[时间复杂度#多项式时间|多项式时间]]方法可以解决最小割问题,最知名的是[[埃德蒙兹-卡普算法]]。<ref>{{citation | last1 = Cormen | first1 = Thomas H. | author1-link = Thomas H. Cormen | last2 = Leiserson | first2 = Charles E. | author2-link = Charles E. Leiserson | last3 = Rivest | first3 = Ronald L. | author3-link = Ronald L. Rivest | last4 = Stein | first4 = Clifford | author4-link = Clifford Stein | edition = 2nd | isbn = 0-262-03293-7 | page = 563,655,1043 | publisher = MIT Press and McGraw-Hill | title = [[Introduction to Algorithms]] | year = 2001}}.</ref> ==最大割== [[File:Max-cut.svg|thumb|right|一个最大割。]] {{main|最大割}} 最大割的大小或权不小于其他割。右图展示了最大割,其大小为5,且没有大小为6的割(即边的总数,写作<math>|E|</math>),因为这张图不是[[二分图]](有[[循环图#术语|奇环]])。 一般来说,找最大割是很难计算的。<ref>{{citation | last1 = Garey | first1 = Michael R. | author1-link = Michael R. Garey | last2 = Johnson | first2 = David S. | author2-link = David S. Johnson | isbn = 0-7167-1045-5 | at = [https://archive.org/details/computersintract0000gare/page/ A2.2: ND16, p. 210] | publisher = W.H. Freeman | title = [[Computers and Intractability: A Guide to the Theory of NP-Completeness]] | year = 1979 }}.</ref> 最大割问题是[[卡普的二十一个NP-完全问题]]之一,<ref>{{citation | last = Karp | first = R. M. | author-link = Richard Karp | editor1-last = Miller | editor1-first = R. E. | editor2-last = Thacher | editor2-first = J. W. | contribution = Reducibility among combinatorial problems | location = New York | pages = 85–103 | publisher = Plenum Press | title = Complexity of Computer Computation | year = 1972}}.</ref> 也是[[APX问题]]之一,这是说除非P = NP,否则不会存在多项式时间复杂度的近似方法。<ref>{{citation | last1 = Khot | first1 = S. | author1-link = Subhash Khot | last2 = Kindler | first2 = G. | last3 = Mossel | first3 = E. | last4 = O’Donnell | first4 = R. | contribution = Optimal inapproximability results for MAX-CUT and other two-variable CSPs? | pages = 146–154 | title = Proceedings of the 45th IEEE Symposium on Foundations of Computer Science | contribution-url = https://www.cs.cmu.edu/~odonnell/papers/maxcut.pdf | year = 2004 | access-date = 2019-08-29 | archive-date = 2019-07-15 | archive-url = https://web.archive.org/web/20190715031206/http://www.cs.cmu.edu/~odonnell/papers/maxcut.pdf | url-status = live }}.</ref> 不过,可以用[[半正定规划]],将其逼近到恒定的[[近似算法#近似比|近似比]]。<ref>{{citation | last1 = Goemans | first1 = M. X. | author1-link = Michel Goemans | last2 = Williamson | first2 = D. P. | author2-link = David P. Williamson | doi = 10.1145/227683.227684 | issue = 6 | journal = [[Journal of the ACM]] | pages = 1115–1145 | title = Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming | volume = 42 | year = 1995| doi-access = free }}.</ref> 注意从[[线性规划]]的意义上讲,最小割与最大割问题虽然可以通过改换[[损失函数|目标函数]]的min、max使其变为另一个问题,但不是[[线性规划#对偶|对偶]]的:最小割问题的对偶实际上是最大流问题。<ref>{{citation | last = Vazirani | first = Vijay V. | author-link = Vijay Vazirani | isbn = 3-540-65367-8 | pages = 97–98 | publisher = Springer | title = Approximation Algorithms | year = 2004}}.</ref> == 最疏割 == '''最疏割'''(sparsest cut)使跨过割的边数对割的较小一侧的顶点数之比最小,目标函数偏向稀疏(跨过割的边更少)与平衡(接近二分)。这是NP问题,已知的最佳近似算法是<math>O(\sqrt{\log n})</math>近似,见{{Harvtxt|Arora|Rao|Vazirani|2009}}。<ref>{{citation | last1 = Arora | first1 = Sanjeev | author1-link = Sanjeev Arora | last2 = Rao | first2 = Satish | last3 = Vazirani | first3 = Umesh | author3-link = Umesh Vazirani | doi = 10.1145/1502793.1502794 | issue = 2 | journal = J. ACM | pages = 1–37 | publisher = ACM | title = Expander flows, geometric embeddings and graph partitioning | volume = 56 | year = 2009| s2cid = 263871111 }}.</ref> == 割空间== 无向图的所有割的族(family)称作图的'''割空间'''(cut space),在算术模2的二元[[有限域]]上形成[[向量空间]],以两割集的[[对称差]]为向量加法,是[[环空间]]的[[正交补]]。<ref name="gy">{{citation | last1 = Gross | first1 = Jonathan L. | last2 = Yellen | first2 = Jay | contribution = 4.6 Graphs and Vector Spaces | edition = 2nd | isbn = 9781584885054 | pages = 197–207 | publisher = CRC Press | title = Graph Theory and Its Applications | url = https://books.google.com/books?id=-7Q_POGh-2cC&pg=PA197 | year = 2005}}.</ref><ref name="diestel">{{citation | last = Diestel | first = Reinhard | contribution = 1.9 Some linear algebra | pages = 23–28 | publisher = Springer | series = Graduate Texts in Mathematics | title = Graph Theory | url = https://books.google.com/books?id=eZi8AAAAQBAJ&pg=PA23 | volume = 173 | year = 2012}}.</ref>若给边赋予正权重,割空间的最小权[[基 (线性代数)|基]]可由与图同顶点集的[[树 (图论)|树]]描述,称作[[最小割树]]。<ref>{{citation | last1 = Korte | first1 = B. H. | author1-link = Bernhard Korte | last2 = Vygen | first2 = Jens | contribution = 8.6 Gomory–Hu Trees | isbn = 978-3-540-71844-4 | pages = 180–186 | publisher = Springer | series = Algorithms and Combinatorics | title = Combinatorial Optimization: Theory and Algorithms | volume = 21 | year = 2008}}.</ref>树的边都关联于原图的键,两节点''s''、''t''之间的最小割也就是与树中''s''到''t''的路径相关联的键中权最小的键。 == 另见 == * [[连通性 (图论)]] * [[裂 (图论)]] * [[顶点割]] * [[桥 (图论)]] * [[割宽]] == 参考 == {{reflist|30em}} {{图论}} [[Category:图的连通性]] [[Category:组合优化]]
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