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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.
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.
Example
Let's again take a look at the network in . Let's first consider the cut \(V=L_1\cup U_1\) with \[\begin{aligned}\end{aligned}\] Here we see that the capacity of the cut is \[\begin{aligned}\end{aligned}\] We must be a bit more careful, however, when we look at the cut \(V=L_2\cup U_2\) with \[\begin{aligned}\end{aligned}\] Here the capacity of the cut is \[\begin{aligned}\end{aligned}\] Notice that we do not include \(c(D,B)\) in the calculation as the directed edge \((D,B)\) is from \(U_2\) to \(L_2\).
The relationship between flows and cuts rests on the following fundamentally important theorem.
Condensed: the full section is in Keller & Trotter, Applied Combinatorics.
Most te. Nincs számológép rendezi ezt, de a darabjai komposztálhatóak. Próbálja ki az egyiket lentebb, vagy gépelje be a sajátját.
Egy ingyenes fiók jegyzeteket ad minden leckéről, egy feljegyzést arról, hogy mit végeztél el, a megoldott problémáidról egy helyen, és egy oktatót, akit megkérdezhetsz erről az oldalról. A matematika maga mindenki számára nyitva áll, bejelentkezve vagy sem.
Regisztrálj! BejelentkezésItt használt szimbólumok
Koppintson a teljes definícióra, a képre és arra, hogy mit jelent minden betű.
Kérdések, amiket az emberek feltesznek
Permutation or combination?
Ask whether order matters. A lock code is a permutation (order matters); a hand of cards is a combination (it does not).
What is a graph in this sense?
Dots (vertices) joined by lines (edges), not a plot. Road maps, social networks and molecules are graphs; questions like "is there a route" and "how few colours" are graph theory.
Az oldal részei adaptálva Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). Össze van zavarodva és újra megmagyarázva; a hibák a miénk.
Még több Combinatorics & Graph Theory
The counting principlesPigeonhole principle and inclusion, exclusionBinomial coefficients and Pascal's triangleRecurrences and generating functionsGraphs: vertices, edges, degreesPaths, cycles, trees, Euler and HamiltonColouring and planar graphs