'Feasible flow' presentation slideshows

Minimum cost flows: basic algorithms (Part II)

Minimum cost flows: basic algorithms (Part II). Adi Haviv (+ Ben Klein) 18/03/2013. Lecture Overview. Introduction (Reminder) Optimality Conditions (Reminder) Pseudo-flow MCF Algorithms: Successive shortest Path Algorithm Primal-Dual Algorithm Out-Of-Kilter Algorithm Summary.

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Lecture 13

Lecture 13. Introduction to Minimum Cost Flows. -. A feasible flow x is optimal for the minimum cost flow problem if and only if some set of node potentials satisfy the following reduced cost optimality conditions: for every arc (i, j) in G(x),. Cycle Canceling Algorithm.

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The Min Cost Flow Problem

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Chapter 6 Maximum Flows: Basic Ideas

Chapter 6 Maximum Flows: Basic Ideas. 6.1 Introduction. Formulation: Maximize v (6.1a) subject to ? {j: (i, j)?A} x ij - ? {j: (j, i)?A} x ji = v, for i = s (6.1b) = 0, for all i ?N{s, t} = -v, for i = t

617 views • 40 slides

15.082 and 6.855J

15.082 and 6.855J. Cycle Canceling Algorithm. A minimum cost flow problem. 0. 0. 10, $4. 2. 4. 30, $7. 25, $5. 25. 1. 20, $2. 20, $6. 20, $1. 3. 5. 25, $2. 0. -25. The Original Capacities and Feasible Flow. 0. 0. 10, 10. 2. 4. 30, 25. 25, 15. 25. 1. 20, 10. 20, 20.

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Minimum Cost Flow

Minimum Cost Flow. Algorithms and Networks. This lecture. The minimum cost flow problem: statement and applications The cycle cancelling algorithm A polynomial time variant of cycle cancelling The successive shortest paths algorithm. Minimum Cost Flow I. Edges have

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A self-stabilizing algorithm for the maximum flow problem

A self-stabilizing algorithm for the maximum flow problem. Sukumar Ghosh, Arobinda Gupta and Sriram V. Pemmaraju. 6 th May 2004. Presented By Niranjan. Paper Outline. Introduction to maximum flow problem Model of computation Maximum flow algorithm for acyclic graphs Proof of correctness

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EMIS 8374 The Maximum Flow Problem: Residual Flows and Networks Updated 3 March 2008

EMIS 8374 The Maximum Flow Problem: Residual Flows and Networks Updated 3 March 2008. The Residual Network. Given a flow x , the residual capacity r ij of arc ( i , j ) is the maximum additional flow that can be sent from i to j using arcs ( i , j ) and ( j , i )

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Feasible Flow

Feasible Flow. Network : A digraph with a nonnegative capacity c(e) on each edge e and a distinguished source node s and sink node t. Flow: A flow f assign a value f(e) to each edge e. f + (v) denotes the total flow on edges leaving v and f - (v) denotes the total flow on edges entering v.

229 views • 10 slides