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today Iamp;#39;m going to talk about the max-flow min-cut theorem it shows the duality between two seemingly different problems the theorem states that the maximum value of a Nestea flow is equal to the minimum capacity over all ST cuts weamp;#39;ll see what that means in a minute but as some motivation that theorem directly implies correctness of the ford-fulkerson algorithm to continue with the motivation letamp;#39;s have a quick look at the algorithm Iamp;#39;m not going to explain the full focus an algorithm in detail so make sure that you have a basic understanding of it before you continue watching you should be familiar with concepts like the residual graph flow conservation and capacity constraints the important part for this video though is the break condition note that the algorithm stops when thereamp;#39;s no augmenting ST path in the residual graph the max-flow min-cut theorem follows from the following theorem which will prove in a second note that if their statemen
