Lecture 13: Incremental Improvement: Max Flow, Min Cut | Design and Analysis of Algorithms | Electrical Engineering and Computer Science | MIT OpenCourseWare

State the maximum-flow problem as a linear-programming problem.... | Filo

Find the maximum directivity and maximum intensity given the pa... | Filo

There are many common variations of the maximum flow problem. Here are four of them. (a) There are many sources and many sinks, and we wish to maximize the total flow from all sources to all sinks. (b) Each vertex also has a capacity on the maximum flow that can enter it. (c) Each edge has not only a capacity, but also a lower bound on the flow it must carry. (d) The outgoing flow from each node u is not the same as the incoming flow, but is smaller by a factor of (1-ϵu), where ϵu is a loss coef

In a standard s-t Maximum-Flow Problem, we assume edges have capaci ties, and there is no limit on how much flow is allowed to pass through a node. In this problem, we consider the variant of the Maximum-Flow and Minimum-Cut problems with node capacities. Let G=(V, E) be a directed graph, with source s ∈V, sink t ∈V, and nonnegative node capacities {cv ≥0} for each v ∈V. Given a flow f in this graph, the flow though a node v is defined as f^in (v). We say that a flow is feasible if it satisfies