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O Autima i Slicno | Theoretical Computer Science | Physics & Mathematics

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nesto o autima i slicno
  MAXIMUM FLOW Max-Flow Min- Cut Theorem (Ford Fukerson’s Algorithm)     What is Network Flow ? Flow network is a directed graph G=(V,E) such that each edge has a non-negative capacity c(u,v) ≥0.  Two distinguished vertices exist in G namely : ã  Source (denoted by s) : In-degree of this vertex is 0. ã  Sink (denoted by t) : Out-degree of this vertex is 0. Flow in a network is an integer-valued function f defined On the edges of G satisfying 0 ≤f(u,v)≤c(u,v), for every Edge (u,v) in E.   What is Network Flow ? ã  Each edge (u,v) has a non-negative capacity c(u,v). ã  If (u,v) is not in E assume c(u,v)=0. ã  We have source s and sink t. ã  Assume that every vertex v in V is on some path from s to t. Following is an illustration of a network flow: c(s,v1)=16 c(v1,s)=0 c(v2,s)=0 …    Conditions for Network Flow For each edge (u,v) in E, the flow f(u,v) is a real valued function that must satisfy following 3 conditions : ã  Skew Symmetry : u,v  V, f(u,v)= -f(v,u) ã  Capacity Constraint :   u,v  V, f(u,v)    c(u,v) ã  Flow Conservation: u  V  –  {s,t}   f(s,v)=0 v  V Skew symmetry condition implies that f(u,u)=0.
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