'Primal dual' presentation slideshows

Duality

Duality. ???. ??????? ?????????. Content. The Dual of an LP in General Form Complementary Slackness The Shortest-Path Problem and Its Dual Dual Information in the Tableau The Dual Simplex Algorithm. Duality. The Dual of an LP in General Form. ??????? ?????????. > <.

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Title Page

An Application of Market Equilibrium in Distributed Load Balancing in Wireless Networking. Title Page. Algorithms and Economics of Networks UW CSE-599m. Reference. Cell-Breathing in Wireless Networks, by Victor Bahl, MohammadTaghi Hajiaghayi, Kamal Jain, Vahab Mirrokni, Lili Qiu, Amin Saberi.

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Approximation Algorithms:

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Model of TCP/AQM & Market Mechanism for Resource Allocation

Model of TCP/AQM & Market Mechanism for Resource Allocation. TCP. TCP. Receiver. Receiver. Internet. Inbound Link. Router. Outbound Link. TCP. TCP. Receiver. Receiver. Internet. Active Queue Management (AQM). Queue. Inbound Link. Router. Outbound Link. Problems.

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Linear Programming

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Linear Programming

Linear Programming. Piyush Kumar (For Class of Dr. Ashok Srinivasan). Welcome to CIS5930-09. Optimization. For example. This is what is known as a standard linear program. Linear Programming. Significance A lot of problems can be converted to LP formulation

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Mechanism design for electronic markets - algorithms and economics

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Lecture 13

Lecture 13. Chapter 7 Duality and Sensitivity in Linear Programming 7.1 Objective values usually can be interpreted as either minimize cost or maximize benefit . 7.3 Page 301 < constraints usually restrict the supply of some commodity

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Linear Programming and Approximation

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Facility Location with Service Installation Costs

Facility Location with Service Installation Costs. Chaitanya Swamy Joint work with David Shmoys and Retsef Levi Cornell University. Facility Location. facility. client. F : set of facilities . D : set of clients . Facility i has facility cost f i .

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Facility Location with Service Installation Costs

Facility Location with Service Installation Costs. Chaitanya Swamy Joint work with David Shmoys and Retsef Levi Cornell University. Facility Location. facility. client. F : set of facilities . D : set of clients . Facility i has facility cost f i .

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Integrated Logistics PROBE

Integrated Logistics PROBE. Princeton University, 10/31-11/1. Presentation Outline. Defining Logistics Applications and Key Problems Facility Location Known Results Open Problems Hierarchical Network Design Known Results Open Problems. Defining Logistics.

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Bandwidth Allocation with Multiple Objectives Or What Can We Do with Per-Flow State?

Bandwidth Allocation with Multiple Objectives Or What Can We Do with Per-Flow State? Ashish Goel Stanford University Joint work with Sung-Woo Cho. http://www.stanford.edu/~ashishg. Window size. t. Bandwidth allocation. Consider N best-effort, long-lived flows sharing the Internet

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A Combinatorial, Primal-Dual Approach to Semidefinite Programs

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Fault-Tolerant Facility Location

Fault-Tolerant Facility Location. Chaitanya Swamy David Shmoys Cornell University. F : set of facilities . D : set of clients . Facility i has facility cost f i . c ij : distance between i and j in V . Client j wants to be connected to r j distinct facilities.

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Lecture 20 Linear Programming

Lecture 20 Linear Programming. II. Duality . Dual LP. Primal. Dual. Lemma. Proof . Duality Theorem. Proof. Theorem. Proof of Duality Theorem:. Dual Simplex Method. Key Facts. Simplex Table. Primal-Dual Method. Complementary Slackness Condition. Remark. Polynomial-Time Algorithms.

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Combinatorial Interpretations of Dual Fitting and Primal Fitting

Combinatorial Interpretations of Dual Fitting and Primal Fitting. Ari Freund Cesarea Rothschild Institute, University of Haifa Dror Rawitz Department of Computer Science, Technion. Approximation Using LP Duality. Minimization problem LP-relaxation and dual:

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Online Multi-Commodity Flow with High Demands

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Primal-dual algorithms for node-weighted network design in planar graphs

Primal-dual algorithms for node-weighted network design in planar graphs. Grigory Yaroslavtsev Penn State (joint work with Piotr Berman). Feedback Vertex Set Problems. Given: a collection of cycles in a graph Goal: break them, removing a small # of vertices.

247 views • 17 slides