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