Flows and Cuts

Considering the applications suggested at the beginning of the chapter, it is natural to ask for the maximum value of a flow in a given network. Put another way, we want to find the largest number \(v_0\) so that there exists a flow \(\phi\) of value \(v_0\) in the network. Of course, we not only want to find the maximum value \(v_0\), but we also want to find a flow \(\phi\) having this value. Although it may seem a bit surprising, we will develop an efficient algorithm which both finds a flow of maximum value and finds a certificate verifying the claim of optimality. This certificate makes use of the following important concept.

A partition \(V=L\cup U\) of the vertex set \(V\) of a network with \(S\in L\) and \(T\in U\) is called a cut.Our choice of \(L\) and \(U\) for the names of the two parts of the partition will make more sense later in the chapter. The capacity of a cut \(V=L\cup U\), denoted \(c(L,U)\), is defined by \[\begin{aligned}\end{aligned}\] Put another way, the capacity of the cut \(V=L\cup U\) is the total capacity of all edges from \(L\) to \(U\). Note that in computing the capacity of the cut \(V=L\cup U\), we only add the capacities of the edges from \(L\) to \(U\). We do not include the edges from \(U\) to \(L\) in this sum.

The relationship between flows and cuts rests on the following fundamentally important theorem.

Condensed: the full section is in Keller & Trotter, Applied Combinatorics.