Bankruptcy Problems and Minimum Cost Flow Problems

Size: px
Start display at page:

Download "Bankruptcy Problems and Minimum Cost Flow Problems"

Transcription

1 Bankrupcy Problem and Minimum Co Flow Problem Rodica Branzei Faculy of Compuer Science, "Alexandru Ioan Cuza" Univeriy, Iai, Romania Giulio Ferrari Univeriy of Genoa, Deparmen of Mahemaic, Genova, Ialy Vio Fragnelli Univeriy of Eaern Piedmon, Deparmen of Advanced Science and Technologie, Aleandria, Ialy Sef Tij CenER and Deparmen of Economeric and Operaion Reearch, Tilburg Univeriy, Tilburg, The Neherland Univeriy of Genoa, Deparmen of Mahemaic, Genova, Ialy AIROWINTER Corina (BL)

2 Bankrupcy Problem and Minimum Co Flow Problem 2 Ouline Join Projec Bankrupcy Problem and Relaed Flow Problem Two Generalized Bankrupcy Problem Bankrupcy Rule and Min Co Flow Problem Concluding Remark

3 Bankrupcy Problem and Minimum Co Flow Problem 3 Join Projec Projec whoe aciviie are carried ou by differen firm Game heoreic approach of raioning problem ariing from join projec managemen: Berganiño and Sánchez (2002): NTU game for allocaing ime Branzei, Ferrari, Fragnelli and Tij (2002): TU game for allocaing co Caro and Tejada (2004): allocaing ime depending on uiliy (ground operaion on aircraf) Branzei, Ferrari, Fragnelli and Tij (2002): Divide he co of he delay of a projec among he aciviie ha have a delay via bankrupcy approach Two new queion: - Wha o do if ome aciviie recover par of he delay? - Wha o do if an exra reward arie from an early erminaion of he projec?

4 Bankrupcy Problem and Minimum Co Flow Problem 4 Bankrupcy Problem and Relaed Flow Problem Claical bankrupcy problem (N,E,c) where N = {1,, n} E R + e of claiman eae o be divided among claiman c =(c 1,, c n ) R n + claim, wih 0 E C = c 1 + c c n A oluion i a real vecor x =(x 1,,x n ) i N x i = E;0 x i c i, i N Sandard flow problem Nework G(N, A) wih wo node, he ource wih no enering arc and he ink wih no ougoing arc; arc have minimal and maximal capaciy conrain A flow i a funcion x : A R + ha repec he capaciy conrain and uch ha j N x ij = j N x ji, i N \{, } A claical bankrupcy problem can be repreened a a andard flow problem E/E 0/c 1 0/c n Each feaible flow correpond o a oluion of he bankrupcy problem

5 Bankrupcy Problem and Minimum Co Flow Problem 5 Two Generalized Bankrupcy Problem Claiman and debor Generalized bankrupcy problem A - The bank ha an eae E (N c,n d,e,c,d) where N c = {1 c,,n c } e of claiman N d = {1 d,, n d } e of debor E R + eae c =(c 1c,, c nc ) R n c + claim, wih 0 E C = c 1c + + c nc d =(d 1d,, d nd ) R n d + deb E/E d 1d d nd c 1c c nc

6 Bankrupcy Problem and Minimum Co Flow Problem 6 The value of E, c and d idenify he following wo ubcae: A1 i N c c i E + i N d d i A2 E i N c c i <E+ i N d d i A1 (eay) (N,E,c ) wih N = N c, E = E + i N d d i, c i = c i, i N c E + / d i E + i Nd i N d d i 0/c 1c 0/c nc

7 Bankrupcy Problem and Minimum Co Flow Problem 7 A2i Allocae he quoa E = i N c c i E,N = N d,c i = d i, i N d / c i E c i E i Nc i N c 0/d 1d 0/d nd A2ii Allocae he aving E = E + i N d d i i N c c i,n = N d,c i = d i, i N d E + d i / c i E + d i i Nd i Nc i N d c i i N c 0/d 1d 0/d nd

8 Bankrupcy Problem and Minimum Co Flow Problem 8 Example 1 Conider a iuaion in which a bank ha an eae E =10; he e of claiman i N c = {1 c, 2 c, 3 c } wih claim vecor c =(5, 6, 7) and he e of debor i N d = {1 d, 2 d } wih deb vecor d =(1, 2) Thi iuaion end in ubcae A1 and he correponding claical bankrupcy problem i (N,E,c ) wih N = {1 c, 2 c, 3 c },E =13,c =(5, 6, 7) If we conider an eae E =16we are in ubcae A2 and he correponding claical bankrupcy problem i (N,E,c ) wih N = {1 d, 2 d },E =2,c =(1, 2) according o he approach A2i or (N,E,c ) wih N = {1 d, 2 d },E =1,c =(1, 2) according o he approach A2ii

9 Bankrupcy Problem and Minimum Co Flow Problem 9 Generalized bankrupcy problem B - The bank ha a deb Ê (N c,n d, Ê,c,d) where N c = {1 c,,n c } e of claiman N d = {1 d,, n d } e of debor Ê R + deb of he bank c =(c 1c,, c nc ) R n c + claim d =(d 1d,, d nd ) R n d + deb, wih 0 Ê D = d 1 d + + d nd d 1d d nd Ê/Ê c 1c c nc

10 Bankrupcy Problem and Minimum Co Flow Problem 10 Again, he value of Ê, c and d idenify he following wo ubcae: B1 if Ê i N d d i < Ê + i N c c i B2 if i N d d i Ê + i N c c i B1 (eay) (N,E,c ) wih N = N c, E = i N d d i Ê, c i = c i, i N c / d i Ê d i Ê i Nd i N d 0/c 1c 0/c nc

11 Bankrupcy Problem and Minimum Co Flow Problem 11 B2i Allocae he quoa (N,E,c ) wih N = N d,e = Ê + i N c c i,c i = d i, i N d Ê + / c i Ê + i Nc i N c c i 0/d 1d 0/d nd B2ii Allocae he aving (N,E,c ) wih N = N d,e = i N d d i (Ê + i N c c i ),c i = d i, i N d d i Ê / c i d i Ê i Nd i Nc i N d i N c c i 0/d 1d 0/d nd

12 Bankrupcy Problem and Minimum Co Flow Problem 12 Example 2 Conider a iuaion in which a bank ha a deb Ê =12; he e of claiman i N c = {1 c, 2 c, 3 c } wih claim vecor c =(3, 4, 5) and he e of debor i N d = {1 d, 2 d } wih deb vecor d =(8, 9) Thi iuaion end in ubcae B1 and he correponding claical bankrupcy problem i (N,E,c ) wih N = {1 c, 2 c, 3 c },E =5,c =(3, 4, 5) If we conider a deb Ê =2we are in ubcae B2 and he correponding claical bankrupcy problem i (N,E,c ) wih N = {1 d, 2 d },E =14,c =(8, 9) according o he approach B2i or (N,E,c ) wih N = {1 d, 2 d },E =3,c =(8, 9) according o he approach B2ii

13 Bankrupcy Problem and Minimum Co Flow Problem 13 Bankrupcy Rule and Min Co Flow Problem A diviion rule i a funcion f which aign o any bankrupcy problem (N,E,c) a vecor f(n,e,c) R n uch ha: 0 f i (N,E,c) c i, for each i N f i (N,E, c) =E i N Well known diviion rule are he proporional rule (PROP), he conrained equalawardrule (CEA), he conrained equal lo rule (CEL),healmudicrule(TAL) and he adjued proporional rule (APROP)

14 Bankrupcy Problem and Minimum Co Flow Problem 14 PROP i (N,E,c) =( j N c j) 1 ci E, i N CEA i (N,E,c) =min{c i,α}, i N where α i he unique real number o ha i N CEA i(n,e, c) =E CEL i (N,E,c) =max{c i β,0}, i N where β i he unique real number o ha i N CEL i(n,e,c) =E { CEA i (N,E, 1 2 TAL i (N,E, c) = c) if E<1 2 j N c j c i CEA i (N,E, 1 2 c) if E 1 2 j N c,i N j where E = j N c j E The minimal righ of each player i N i m i (N,E,c) =max{0,e j N\{i} c j}, i N AP ROP i (N,E,c) =m i (N,E,c)+PROP i (N,E,c ),i N where E = E j N m j and c i = min{e,c i m i (N,E,c)}, i N A claical bankrupcy problem (N,E, c) and a diviion rule f can be relaed o a min co flow problem

15 Bankrupcy Problem and Minimum Co Flow Problem 15 Theorem 1 Le (N,E,c) be a claical bankrupcy problem The diviion rule PROP, CEA, CEL and TAL can be implemened via a min co flow problem Proof We only give for each rule a e of uiable co funcion PROP: k i (x i )= x2 i c i CEA: k i (x i )=x 2 i CEL: k i (x i )=(c i x i ) 2 For he Talmudic rule if E< 1 2 i N c i: TAL: k i (x i )=x 2 i,i N eing he maximal capaciy of he arc correponding o he claiman o 1 2 c i If E 1 2 i N c i: TAL: k i (x i )=(c i x i ) 2,i N eing he minimal capaciy of he arc correponding o he claiman o 1 2 c i

16 Bankrupcy Problem and Minimum Co Flow Problem 16 Remark 1 Le (N,E, c) be a claical bankrupcy problem The oluion APROP(N,E,c) can be obained via a min co flow problem wih e of co funcion: 0 if x i m i k i (x i )= (x i m i ) 2,i N c i m if x i >m i i

17 Bankrupcy Problem and Minimum Co Flow Problem 17 Concluding Remark Paricular choice of co funcion in a min co flow problem can lead o oher rule from he bankrupcy lieraure, or ugge new diviion according o differen fairne crieria, ailoring he amoun on each agen E/E d 1d d nd c 1c c nc Ê/Ê d 1d d nd c 1c c nc Bankrupcy approach aurae arc relaed o claiman or debor Min co flow approach may drive he oluion oward non-auraion of hee arc A muli-claim bankrupcy problem and/or an inerval bankrupcy iuaion can be repreened by an appropriae flow problem

18 Bankrupcy Problem and Minimum Co Flow Problem 17 Reference Aumann, RJ and M Machler (1985) Game Theoreic Analyi of a Bankrupcy Problem from he Talmud J Economic Theory 36, Berganiño, G and E Sánchez (2002) How o Diribue Co Aociaed wih a Delayed Projec Annal of Op Re 109, Borm, P, H Hamer and R Hendrickx (2001) Operaion Reearch Game: A Survey TOP 9, Branzei, R, G Ferrari, V Fragnelli and S Tij (2002) Two Approache o he Problem of Sharing Delay Co in Join Projec Annal of Op Re 109, Branzei, R, D Dimirov and S Tij (2003) Shapley-like Value for Inerval Bankrupcy Game Economic Bullein 3, 1-8 Branzei, R, G Ferrari, V Fragnelli and S Tij (2004) Join Projec Managemen wih Penalie and Compenaion Preprin, Diparimeno di Maemaica dell Univerià digenova519 Caro, J and J Tejada (2004) Una regla proporional a la duracione para el reparo de holgura en un problema PERT Working Paper Curiel, IJ, M Machler and SH Tij (1987) Bankrupcy Game Zeichrif für OR 31, Gondran, M and M Minoux (1984) Graph and Algorihm New York: Wiley Inercience Kaminki, MM (2000) Hydraulic Raioning MahSocSci40, O Neill, B (1982) A Problem of Righ Arbiraion from he Talmud MahSocSci2, Thomon, W (2003) Axiomaic and Game-heoreic Analyi of Bankrupcy and Taxaion Problem: A Survey MahSocSci45, Young, HP (1987) On Dividing an Amoun According o Individual Claim or Liabiliie Mah Op Re 12, Young, HP (1994) Co Allocaion In: RJ Aumann and S Har (Ed), Handbook of Game Theory, vol II, Amerdam: Norh Holland, Young, HP (1998) Diribuive Juice in Taxaion J Economic Theory 48,

19

On Bankruptcy Game Theoretic Interval Rules

On Bankruptcy Game Theoretic Interval Rules On Bankruptcy Game Theoretic Interval Rules arxiv:1301.3096v1 [q-fin.gn] 7 Jan 2013 Rodica Branzei University Alexandru Ioan Cuza, Iaşi, Romania branzeir@info.uaic.ro Marco Dall Aglio Luiss University,

More information

4/12/12. Applications of the Maxflow Problem 7.5 Bipartite Matching. Bipartite Matching. Bipartite Matching. Bipartite matching: the flow network

4/12/12. Applications of the Maxflow Problem 7.5 Bipartite Matching. Bipartite Matching. Bipartite Matching. Bipartite matching: the flow network // Applicaion of he Maxflow Problem. Biparie Maching Biparie Maching Biparie maching. Inpu: undireced, biparie graph = (, E). M E i a maching if each node appear in a mo one edge in M. Max maching: find

More information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

Algorithm Design and Analysis

Algorithm Design and Analysis Algorihm Deign and Analyi LECTURES 17 Nework Flow Dualiy of Max Flow and Min Cu Algorihm: Ford-Fulkeron Capaciy Scaling Sofya Rakhodnikova S. Rakhodnikova; baed on lide by E. Demaine, C. Leieron, A. Smih,

More information

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1 Conider he following flow nework CS444/944 Analyi of Algorihm II Soluion for Aignmen (0 mark) In he following nework a minimum cu ha capaciy 0 Eiher prove ha hi aemen i rue, or how ha i i fale Uing he

More information

Shapley like values for interval bankruptcy games. Abstract

Shapley like values for interval bankruptcy games. Abstract Shapley like values for interval bankruptcy games Rodica Branzei Faculty of Computer Science, Alexandru Ioan Cuza University, Iasi, Romania Dinko Dimitrov CentER and Department of Econometrics and Operations

More information

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t)

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t) /0/ dmin lunch oday rading MX LOW PPLIION 0, pring avid Kauchak low graph/nework low nework direced, weighed graph (V, ) poiive edge weigh indicaing he capaciy (generally, aume ineger) conain a ingle ource

More information

Network Flow. Data Structures and Algorithms Andrei Bulatov

Network Flow. Data Structures and Algorithms Andrei Bulatov Nework Flow Daa Srucure and Algorihm Andrei Bulao Algorihm Nework Flow 24-2 Flow Nework Think of a graph a yem of pipe We ue hi yem o pump waer from he ource o ink Eery pipe/edge ha limied capaciy Flow

More information

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

1 Motivation and Basic Definitions

1 Motivation and Basic Definitions CSCE : Deign and Analyi of Algorihm Noe on Max Flow Fall 20 (Baed on he preenaion in Chaper 26 of Inroducion o Algorihm, 3rd Ed. by Cormen, Leieron, Rive and Sein.) Moivaion and Baic Definiion Conider

More information

Today s topics. CSE 421 Algorithms. Problem Reduction Examples. Problem Reduction. Undirected Network Flow. Bipartite Matching. Problem Reductions

Today s topics. CSE 421 Algorithms. Problem Reduction Examples. Problem Reduction. Undirected Network Flow. Bipartite Matching. Problem Reductions Today opic CSE Algorihm Richard Anderon Lecure Nework Flow Applicaion Prolem Reducion Undireced Flow o Flow Biparie Maching Dijoin Pah Prolem Circulaion Loweround conrain on flow Survey deign Prolem Reducion

More information

Network Flows UPCOPENCOURSEWARE number 34414

Network Flows UPCOPENCOURSEWARE number 34414 Nework Flow UPCOPENCOURSEWARE number Topic : F.-Javier Heredia Thi work i licened under he Creaive Common Aribuion- NonCommercial-NoDeriv. Unpored Licene. To view a copy of hi licene, vii hp://creaivecommon.org/licene/by-nc-nd/./

More information

18 Extensions of Maximum Flow

18 Extensions of Maximum Flow Who are you?" aid Lunkwill, riing angrily from hi ea. Wha do you wan?" I am Majikhie!" announced he older one. And I demand ha I am Vroomfondel!" houed he younger one. Majikhie urned on Vroomfondel. I

More information

Main Reference: Sections in CLRS.

Main Reference: Sections in CLRS. Maximum Flow Reied 09/09/200 Main Reference: Secion 26.-26. in CLRS. Inroducion Definiion Muli-Source Muli-Sink The Ford-Fulkeron Mehod Reidual Nework Augmening Pah The Max-Flow Min-Cu Theorem The Edmond-Karp

More information

Graphs III - Network Flow

Graphs III - Network Flow Graph III - Nework Flow Flow nework eup graph G=(V,E) edge capaciy w(u,v) 0 - if edge doe no exi, hen w(u,v)=0 pecial verice: ource verex ; ink verex - no edge ino and no edge ou of Aume every verex v

More information

Maximum Flow and Minimum Cut

Maximum Flow and Minimum Cut // Sovie Rail Nework, Maximum Flow and Minimum Cu Max flow and min cu. Two very rich algorihmic problem. Cornerone problem in combinaorial opimizaion. Beauiful mahemaical dualiy. Nework Flow Flow nework.

More information

Soviet Rail Network, 1955

Soviet Rail Network, 1955 Sovie Rail Nework, 1 Reference: On he hiory of he ranporaion and maximum flow problem. Alexander Schrijver in Mah Programming, 1: 3,. Maximum Flow and Minimum Cu Max flow and min cu. Two very rich algorihmic

More information

Soviet Rail Network, 1955

Soviet Rail Network, 1955 7.1 Nework Flow Sovie Rail Nework, 19 Reerence: On he hiory o he ranporaion and maximum low problem. lexander Schrijver in Mah Programming, 91: 3, 00. (See Exernal Link ) Maximum Flow and Minimum Cu Max

More information

Flow Networks. Ma/CS 6a. Class 14: Flow Exercises

Flow Networks. Ma/CS 6a. Class 14: Flow Exercises 0/0/206 Ma/CS 6a Cla 4: Flow Exercie Flow Nework A flow nework i a digraph G = V, E, ogeher wih a ource verex V, a ink verex V, and a capaciy funcion c: E N. Capaciy Source 7 a b c d e Sink 0/0/206 Flow

More information

Matching. Slides designed by Kevin Wayne.

Matching. Slides designed by Kevin Wayne. Maching Maching. Inpu: undireced graph G = (V, E). M E i a maching if each node appear in a mo edge in M. Max maching: find a max cardinaliy maching. Slide deigned by Kevin Wayne. Biparie Maching Biparie

More information

Reminder: Flow Networks

Reminder: Flow Networks 0/0/204 Ma/CS 6a Cla 4: Variou (Flow) Execie Reminder: Flow Nework A flow nework i a digraph G = V, E, ogeher wih a ource verex V, a ink verex V, and a capaciy funcion c: E N. Capaciy Source 7 a b c d

More information

! Abstraction for material flowing through the edges. ! G = (V, E) = directed graph, no parallel edges.

! Abstraction for material flowing through the edges. ! G = (V, E) = directed graph, no parallel edges. Sovie Rail Nework, haper Nework Flow Slide by Kevin Wayne. opyrigh Pearon-ddion Weley. ll righ reerved. Reference: On he hiory of he ranporaion and maximum flow problem. lexander Schrijver in Mah Programming,

More information

Greedy. I Divide and Conquer. I Dynamic Programming. I Network Flows. Network Flow. I Previous topics: design techniques

Greedy. I Divide and Conquer. I Dynamic Programming. I Network Flows. Network Flow. I Previous topics: design techniques Algorihm Deign Technique CS : Nework Flow Dan Sheldon April, reedy Divide and Conquer Dynamic Programming Nework Flow Comparion Nework Flow Previou opic: deign echnique reedy Divide and Conquer Dynamic

More information

Selfish Routing. Tim Roughgarden Cornell University. Includes joint work with Éva Tardos

Selfish Routing. Tim Roughgarden Cornell University. Includes joint work with Éva Tardos Selfih Rouing Tim Roughgarden Cornell Univeriy Include join work wih Éva Tardo 1 Which roue would you chooe? Example: one uni of raffic (e.g., car) wan o go from o delay = 1 hour (no congeion effec) long

More information

ARTIFICIAL INTELLIGENCE. Markov decision processes

ARTIFICIAL INTELLIGENCE. Markov decision processes INFOB2KI 2017-2018 Urech Univeriy The Neherland ARTIFICIAL INTELLIGENCE Markov deciion procee Lecurer: Silja Renooij Thee lide are par of he INFOB2KI Coure Noe available from www.c.uu.nl/doc/vakken/b2ki/chema.hml

More information

Algorithm Design and Analysis

Algorithm Design and Analysis Algorihm Deign and Analyi LECTURE 0 Nework Flow Applicaion Biparie maching Edge-dijoin pah Adam Smih 0//0 A. Smih; baed on lide by E. Demaine, C. Leieron, S. Rakhodnikova, K. Wayne La ime: Ford-Fulkeron

More information

No THE TWO-STAGE CONSTRAINED EQUAL AWARDS AND LOSSES RULES FOR MULTI-ISSUE ALLOCATION SITUATIONS

No THE TWO-STAGE CONSTRAINED EQUAL AWARDS AND LOSSES RULES FOR MULTI-ISSUE ALLOCATION SITUATIONS No. 2005 80 THE TWO-STAGE CONSTRAINED EQUAL AWARDS AND LOSSES RULES FOR MULTI-ISSUE ALLOCATION SITUATIONS By Silvia Lorenzo-Freire, Balbina Casas-Méndez, Ruud Hendrickx June 2005 ISSN 0924-7815 The two-stage

More information

6/3/2009. CS 244 Algorithm Design Instructor: t Artur Czumaj. Lecture 8 Network flows. Maximum Flow and Minimum Cut. Minimum Cut Problem.

6/3/2009. CS 244 Algorithm Design Instructor: t Artur Czumaj. Lecture 8 Network flows. Maximum Flow and Minimum Cut. Minimum Cut Problem. Maximum Flow and Minimum Cu CS lgorihm Deign Inrucor: rur Czumaj Lecure Nework Max and min cu. Two very rich algorihmic problem. Cornerone problem in combinaorial opimizaion. Beauiful mahemaical dualiy.

More information

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001 CS 545 Flow Nework lon Efra Slide courey of Charle Leieron wih mall change by Carola Wenk Flow nework Definiion. flow nework i a direced graph G = (V, E) wih wo diinguihed verice: a ource and a ink. Each

More information

No PROJECT GAMES. By Arantza Estévez- Fernández, Peter Borm, Herbert Hamers. July 2005 ISSN

No PROJECT GAMES. By Arantza Estévez- Fernández, Peter Borm, Herbert Hamers. July 2005 ISSN No. 2005 91 PROJECT GAMES By Arantza Estévez- Fernández, Peter Borm, Herbert Hamers July 2005 ISSN 0924-7815 Project games Arantza Estévez-Fernández Peter Borm Herbert Hamers CentER and Department of Econometrics

More information

Price of Stability and Introduction to Mechanism Design

Price of Stability and Introduction to Mechanism Design Algorihmic Game Theory Summer 2017, Week 5 ETH Zürich Price of Sabiliy and Inroducion o Mechanim Deign Paolo Penna Thi i he lecure where we ar deigning yem which involve elfih player. Roughly peaking,

More information

NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY

NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY Ian Crawford THE INSTITUTE FOR FISCAL STUDIES DEPARTMENT OF ECONOMICS, UCL cemmap working paper CWP02/04 Neceary and Sufficien Condiion for Laen

More information

CSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it

CSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it CSC 36S Noe Univeriy of Torono, Spring, 2003 Flow Algorihm The nework we will conider are direced graph, where each edge ha aociaed wih i a nonnegaive capaciy. The inuiion i ha if edge (u; v) ha capaciy

More information

Minimal Overlap Rules for Bankruptcy

Minimal Overlap Rules for Bankruptcy International Mathematical Forum,, 7, no. 6, - Minimal Overlap Rules for Bankruptcy Ruud Hendrickx, Peter Borm, Roel van Elk and Marieke Quant Center and Department of Econometrics and Operations Research

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Civil and Environmental Engineering

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Civil and Environmental Engineering MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deparmen of Civil and Environmenal Engineering 1.731 Waer Reource Syem Lecure 17 River Bain Planning Screening Model Nov. 7 2006 River Bain Planning River bain planning

More information

Today: Max Flow Proofs

Today: Max Flow Proofs Today: Max Flow Proof COSC 58, Algorihm March 4, 04 Many of hee lide are adaped from everal online ource Reading Aignmen Today cla: Chaper 6 Reading aignmen for nex cla: Chaper 7 (Amorized analyi) In-Cla

More information

Selfish Routing and the Price of Anarchy. Tim Roughgarden Cornell University

Selfish Routing and the Price of Anarchy. Tim Roughgarden Cornell University Selfih Rouing and he Price of Anarchy Tim Roughgarden Cornell Univeriy 1 Algorihm for Self-Inereed Agen Our focu: problem in which muliple agen (people, compuer, ec.) inerac Moivaion: he Inerne decenralized

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

6.8 Laplace Transform: General Formulas

6.8 Laplace Transform: General Formulas 48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy

More information

Network Flow Applications

Network Flow Applications Hopial problem Neork Flo Applicaion Injured people: n Hopial: k Each peron need o be brough o a hopial no more han 30 minue aay Each hopial rea no more han n/k" people Gien n, k, and informaion abou people

More information

CSE 521: Design & Analysis of Algorithms I

CSE 521: Design & Analysis of Algorithms I CSE 52: Deign & Analyi of Algorihm I Nework Flow Paul Beame Biparie Maching Given: A biparie graph G=(V,E) M E i a maching in G iff no wo edge in M hare a verex Goal: Find a maching M in G of maximum poible

More information

20/20 20/20 0/5 0/5 20/20 20/20 5/5 0/5 0/5 5/5 0/20 25/30 20/20 30/30 20/20 0/5 5/5 20/20 0/5 0/5 15/20 15/25 20/20 10/10

20/20 20/20 0/5 0/5 20/20 20/20 5/5 0/5 0/5 5/5 0/20 25/30 20/20 30/30 20/20 0/5 5/5 20/20 0/5 0/5 15/20 15/25 20/20 10/10 Annoncemen CSEP Applied Algorihm Richard Anderon Lecre 9 Nework Flow Applicaion Reading for hi week 7.-7.. Nework flow applicaion Nex week: Chaper 8. NP-Compleene Final exam, March 8, 6:0 pm. A UW. hor

More information

Compromise Stable TU-Games Quant, Marieke; Borm, Peter; Reijnierse, Hans; van Velzen, S.

Compromise Stable TU-Games Quant, Marieke; Borm, Peter; Reijnierse, Hans; van Velzen, S. Tilburg University Compromise Stable TU-Games Quant, Marieke; Borm, Peter; Reijnierse, Hans; van Velzen, S. Publication date: 2003 Link to publication Citation for published version (APA): Quant, M., Borm,

More information

Lower and Upper Approximation of Fuzzy Ideals in a Semiring

Lower and Upper Approximation of Fuzzy Ideals in a Semiring nernaional Journal of Scienific & Engineering eearch, Volume 3, ue, January-0 SSN 9-558 Lower and Upper Approximaion of Fuzzy deal in a Semiring G Senhil Kumar, V Selvan Abrac n hi paper, we inroduce he

More information

Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Capacity Constraints

Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Capacity Constraints IJCSI Inernaional Journal of Compuer Science Issues, Vol 9, Issue 1, No 1, January 2012 wwwijcsiorg 18 Applying Geneic Algorihms for Invenory Lo-Sizing Problem wih Supplier Selecion under Sorage Capaciy

More information

ANALYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS

ANALYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS ANAYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS Shang iqun, Zhang Yan, Cheng Gang School of Elecrical and Conrol Engineering, Xi an Univeriy of Science & Technology, 710054, Xi an, China,

More information

Classification of 3-Dimensional Complex Diassociative Algebras

Classification of 3-Dimensional Complex Diassociative Algebras Malayian Journal of Mahemaical Science 4 () 41-54 (010) Claificaion of -Dimenional Complex Diaociaive Algebra 1 Irom M. Rihiboev, Iamiddin S. Rahimov and Wiriany Bari 1,, Iniue for Mahemaical Reearch,,

More information

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

Research Article On Double Summability of Double Conjugate Fourier Series

Research Article On Double Summability of Double Conjugate Fourier Series Inernaional Journal of Mahemaic and Mahemaical Science Volume 22, Aricle ID 4592, 5 page doi:.55/22/4592 Reearch Aricle On Double Summabiliy of Double Conjugae Fourier Serie H. K. Nigam and Kuum Sharma

More information

Performance Comparison of LCMV-based Space-time 2D Array and Ambiguity Problem

Performance Comparison of LCMV-based Space-time 2D Array and Ambiguity Problem Inernaional journal of cience Commerce and umaniie Volume No 2 No 3 April 204 Performance Comparion of LCMV-baed pace-ime 2D Arra and Ambigui Problem 2 o uan Chang and Jin hinghia Deparmen of Communicaion

More information

They were originally developed for network problem [Dantzig, Ford, Fulkerson 1956]

They were originally developed for network problem [Dantzig, Ford, Fulkerson 1956] 6. Inroducion... 6. The primal-dual algorihmn... 6 6. Remark on he primal-dual algorihmn... 7 6. A primal-dual algorihmn for he hore pah problem... 8... 9 6.6 A primal-dual algorihmn for he weighed maching

More information

Explicit form of global solution to stochastic logistic differential equation and related topics

Explicit form of global solution to stochastic logistic differential equation and related topics SAISICS, OPIMIZAION AND INFOMAION COMPUING Sa., Opim. Inf. Compu., Vol. 5, March 17, pp 58 64. Publihed online in Inernaional Academic Pre (www.iapre.org) Explici form of global oluion o ochaic logiic

More information

Competitive and Cooperative Inventory Policies in a Two-Stage Supply-Chain

Competitive and Cooperative Inventory Policies in a Two-Stage Supply-Chain Compeiive and Cooperaive Invenory Policies in a Two-Sage Supply-Chain (G. P. Cachon and P. H. Zipkin) Presened by Shruivandana Sharma IOE 64, Supply Chain Managemen, Winer 2009 Universiy of Michigan, Ann

More information

Inequality measures for intersecting Lorenz curves: an alternative weak ordering

Inequality measures for intersecting Lorenz curves: an alternative weak ordering h Inernaional Scienific Conference Financial managemen of Firms and Financial Insiuions Osrava VŠB-TU of Osrava, Faculy of Economics, Deparmen of Finance 7 h 8 h Sepember 25 Absrac Inequaliy measures for

More information

Examples of Dynamic Programming Problems

Examples of Dynamic Programming Problems M.I.T. 5.450-Fall 00 Sloan School of Managemen Professor Leonid Kogan Examples of Dynamic Programming Problems Problem A given quaniy X of a single resource is o be allocaed opimally among N producion

More information

Product differentiation

Product differentiation differeniaion Horizonal differeniaion Deparmen of Economics, Universiy of Oslo ECON480 Spring 010 Las modified: 010.0.16 The exen of he marke Differen producs or differeniaed varians of he same produc

More information

Average Case Lower Bounds for Monotone Switching Networks

Average Case Lower Bounds for Monotone Switching Networks Average Cae Lower Bound for Monoone Swiching Nework Yuval Filmu, Toniann Piai, Rober Robere, Sephen Cook Deparmen of Compuer Science Univeriy of Torono Monoone Compuaion (Refreher) Monoone circui were

More information

Algorithms. Algorithms 6.4 MAXIMUM FLOW

Algorithms. Algorithms 6.4 MAXIMUM FLOW Algorihm ROBERT SEDGEWICK KEVIN WAYNE 6.4 MAXIMUM FLOW Algorihm F O U R T H E D I T I O N ROBERT SEDGEWICK KEVIN WAYNE hp://alg4.c.princeon.edu inroducion Ford Fulkeron algorihm maxflow mincu heorem analyi

More information

FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER

FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER #A30 INTEGERS 10 (010), 357-363 FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER Nahan Kaplan Deparmen of Mahemaic, Harvard Univeriy, Cambridge, MA nkaplan@mah.harvard.edu Received: 7/15/09, Revied:

More information

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov)

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov) Algorihm and Daa Srucure 2011/ Week Soluion (Tue 15h - Fri 18h No) 1. Queion: e are gien 11/16 / 15/20 8/13 0/ 1/ / 11/1 / / To queion: (a) Find a pair of ube X, Y V uch ha f(x, Y) = f(v X, Y). (b) Find

More information

A Guided Tour in the Topos of Graphs

A Guided Tour in the Topos of Graphs A Guided Tour in he Topo of Graph Sebaiano Vigna Abrac In hi paper we urvey he fundamenal conrucion of a preheaf opo in he cae of he elemenary opo of graph. We prove ha he raniion graph of nondeerminiic

More information

7.5 Bipartite Matching. Chapter 7. Network Flow. Matching. Bipartite Matching

7.5 Bipartite Matching. Chapter 7. Network Flow. Matching. Bipartite Matching Chaper. Biparie Maching Nework Flow Slide by Kein Wayne. Copyrigh 00 Pearon-Addion Weley. All righ reered. Maching Biparie Maching Maching. Inpu: undireced graph G = (V, E). M E i a maching if each node

More information

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen

More information

4.2 The Fourier Transform

4.2 The Fourier Transform 4.2. THE FOURIER TRANSFORM 57 4.2 The Fourier Transform 4.2.1 Inroducion One way o look a Fourier series is ha i is a ransformaion from he ime domain o he frequency domain. Given a signal f (), finding

More information

7.5 Bipartite Matching. Chapter 7. Network Flow. Matching. Bipartite Matching

7.5 Bipartite Matching. Chapter 7. Network Flow. Matching. Bipartite Matching Chaper. Biparie Maching Nework Flow Slide by Kevin Wayne. Copyrigh PearonAddion Weley. All righ reerved. Maching Biparie Maching Maching. Inpu: undireced graph G = (V, E). M E i a maching if each node

More information

MAXIMUM FLOW. introduction Ford-Fulkerson algorithm maxflow-mincut theorem

MAXIMUM FLOW. introduction Ford-Fulkerson algorithm maxflow-mincut theorem MAXIMUM FLOW inroducion Ford-Fulkeron algorihm maxflow-mincu heorem Mincu problem Inpu. An edge-weighed digraph, ource verex, and arge verex. each edge ha a poiive capaciy capaciy 9 10 4 15 15 10 5 8 10

More information

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

!!#$%&#'()!#&'(*%)+,&',-)./0)1-*23) "#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5

More information

Bipartite Matching. Matching. Bipartite Matching. Maxflow Formulation

Bipartite Matching. Matching. Bipartite Matching. Maxflow Formulation Mching Inpu: undireced grph G = (V, E). Biprie Mching Inpu: undireced, biprie grph G = (, E).. Mching Ern Myr, Hrld äcke Biprie Mching Inpu: undireced, biprie grph G = (, E). Mflow Formulion Inpu: undireced,

More information

FRACTIONAL HERMITE-HADAMARD INEQUALITIES FOR SOME CLASSES OF DIFFERENTIABLE PREINVEX FUNCTIONS

FRACTIONAL HERMITE-HADAMARD INEQUALITIES FOR SOME CLASSES OF DIFFERENTIABLE PREINVEX FUNCTIONS U.P.B. Sci. Bull., Serie A, Vol. 78, I. 3, 6 ISSN 3-77 FRACTIONAL HERMITE-HADAMARD INEQUALITIES FOR SOME CLASSES OF DIFFERENTIABLE PREINVEX FUNCTIONS Muhammad Alam NOOR, Khalida Inaya NOOR, Marcela V.

More information

Suggested Solutions to Midterm Exam Econ 511b (Part I), Spring 2004

Suggested Solutions to Midterm Exam Econ 511b (Part I), Spring 2004 Suggeed Soluion o Miderm Exam Econ 511b (Par I), Spring 2004 1. Conider a compeiive equilibrium neoclaical growh model populaed by idenical conumer whoe preference over conumpion ream are given by P β

More information

CS 473G Lecture 15: Max-Flow Algorithms and Applications Fall 2005

CS 473G Lecture 15: Max-Flow Algorithms and Applications Fall 2005 CS 473G Lecure 1: Max-Flow Algorihm and Applicaion Fall 200 1 Max-Flow Algorihm and Applicaion (November 1) 1.1 Recap Fix a direced graph G = (V, E) ha doe no conain boh an edge u v and i reveral v u,

More information

Convex Interval Games

Convex Interval Games Convex Interval Games S.Z. Alparslan Gök R. Branzei S. Tijs Abstract In this paper, convex interval games are introduced and characterizations are given. Some economic situations leading to convex interval

More information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

THE INFLUENCE OF PIT COAL BURNING AND QUALITY IN DOMESTIC STOVE

THE INFLUENCE OF PIT COAL BURNING AND QUALITY IN DOMESTIC STOVE Annal o he Univeriy o Peroşani, Mechanical Engineering, 5 (0, -7 THE INFLUENCE OF PIT COAL BURNING AND QUALITY IN DOMESTIC STOVE GHEORGHE LAURENŢIU DOBREI, TRAIAN VASIU, IOAN CONŢ, CLAUDIU CRIŞAN 4 ove.

More information

April 3, The maximum flow problem. See class notes on website.

April 3, The maximum flow problem. See class notes on website. 5.05 April, 007 The maximum flow problem See cla noe on webie. Quoe of he day You ge he maxx for he minimum a TJ Maxx. -- ad for a clohing ore Thi wa he mo unkinde cu of all -- Shakepeare in Juliu Caear

More information

Intermediate Macro In-Class Problems

Intermediate Macro In-Class Problems Inermediae Macro In-Class Problems Exploring Romer Model June 14, 016 Today we will explore he mechanisms of he simply Romer model by exploring how economies described by his model would reac o exogenous

More information

The Residual Graph. 12 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm

The Residual Graph. 12 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm Augmening Pah Algorihm Greedy-algorihm: ar wih f (e) = everywhere find an - pah wih f (e) < c(e) on every edge augmen flow along he pah repea a long a poible The Reidual Graph From he graph G = (V, E,

More information

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t Lecure 6. Luca and Sokey: Opimal Moneary and Fical Policy in an Economy wihou Capial (JME 983. A argued in Kydland and Preco (JPE 977, Opimal governmen policy i likely o be ime inconien. Fiher (JEDC 98

More information

An Inventory Replenishment Model for Deteriorating Items with Time-varying Demand and Shortages using Genetic Algorithm

An Inventory Replenishment Model for Deteriorating Items with Time-varying Demand and Shortages using Genetic Algorithm An Invenory Replenihmen odel for Deerioraing Iem wih ime-varying Demand and Shorage uing Geneic Algorihm An Invenory Replenihmen odel for Deerioraing Iem wih ime-varying Demand and Shorage uing Geneic

More information

Application of a Stochastic-Fuzzy Approach to Modeling Optimal Discrete Time Dynamical Systems by Using Large Scale Data Processing

Application of a Stochastic-Fuzzy Approach to Modeling Optimal Discrete Time Dynamical Systems by Using Large Scale Data Processing Applicaion of a Sochasic-Fuzzy Approach o Modeling Opimal Discree Time Dynamical Sysems by Using Large Scale Daa Processing AA WALASZE-BABISZEWSA Deparmen of Compuer Engineering Opole Universiy of Technology

More information

Max Flow, Min Cut COS 521. Kevin Wayne Fall Soviet Rail Network, Cuts. Minimum Cut Problem. Flow network.

Max Flow, Min Cut COS 521. Kevin Wayne Fall Soviet Rail Network, Cuts. Minimum Cut Problem. Flow network. Sovie Rail Nework, Max Flow, Min u OS Kevin Wayne Fall Reference: On he hiory of he ranporaion and maximum flow problem. lexander Schrijver in Mah Programming, :,. Minimum u Problem u Flow nework.! Digraph

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 7: SECOND-ORDER CIRCUITS EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha

More information

18.03SC Unit 3 Practice Exam and Solutions

18.03SC Unit 3 Practice Exam and Solutions Sudy Guide on Sep, Dela, Convoluion, Laplace You can hink of he ep funcion u() a any nice mooh funcion which i for < a and for > a, where a i a poiive number which i much maller han any ime cale we care

More information

On the Exponential Operator Functions on Time Scales

On the Exponential Operator Functions on Time Scales dvance in Dynamical Syem pplicaion ISSN 973-5321, Volume 7, Number 1, pp. 57 8 (212) hp://campu.m.edu/ada On he Exponenial Operaor Funcion on Time Scale laa E. Hamza Cairo Univeriy Deparmen of Mahemaic

More information

Intermediate Solutions for Emden Fowler Type Equations: Continuous Versus Discrete 1

Intermediate Solutions for Emden Fowler Type Equations: Continuous Versus Discrete 1 Advance in Dynamical Syem and Applicaion. ISSN 973-5321 Volume 3 Number 1 (28), pp. 161 176 Reearch India Publicaion hp://www.ripublicaion.com/ada.hm Inermediae Soluion for Emden Fowler Type Equaion: Coninuou

More information

Math 10C: Relations and Functions PRACTICE EXAM

Math 10C: Relations and Functions PRACTICE EXAM Mah C: Relaions and Funcions PRACTICE EXAM. Cailin rides her bike o school every day. The able of values shows her disance from home as ime passes. An equaion ha describes he daa is: ime (minues) disance

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V ME 352 VETS 2. VETS Vecor algebra form he mahemaical foundaion for kinemaic and dnamic. Geomer of moion i a he hear of boh he kinemaic and dnamic of mechanical em. Vecor anali i he imehonored ool for decribing

More information

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER John Riley 6 December 200 NWER TO ODD NUMBERED EXERCIE IN CHPTER 7 ecion 7 Exercie 7-: m m uppoe ˆ, m=,, M (a For M = 2, i i eay o how ha I implie I From I, for any probabiliy vecor ( p, p 2, 2 2 ˆ ( p,

More information

Suggested Practice Problems (set #2) for the Physics Placement Test

Suggested Practice Problems (set #2) for the Physics Placement Test Deparmen of Physics College of Ars and Sciences American Universiy of Sharjah (AUS) Fall 014 Suggesed Pracice Problems (se #) for he Physics Placemen Tes This documen conains 5 suggesed problems ha are

More information

Stability in Distribution for Backward Uncertain Differential Equation

Stability in Distribution for Backward Uncertain Differential Equation Sabiliy in Diribuion for Backward Uncerain Differenial Equaion Yuhong Sheng 1, Dan A. Ralecu 2 1. College of Mahemaical and Syem Science, Xinjiang Univeriy, Urumqi 8346, China heng-yh12@mail.inghua.edu.cn

More information

Maximum Flow in Planar Graphs

Maximum Flow in Planar Graphs Maximum Flow in Planar Graph Planar Graph and i Dual Dualiy i defined for direced planar graph a well Minimum - cu in undireced planar graph An - cu (undireced graph) An - cu The dual o he cu Cu/Cycle

More information

Research Article An Upper Bound on the Critical Value β Involved in the Blasius Problem

Research Article An Upper Bound on the Critical Value β Involved in the Blasius Problem Hindawi Publihing Corporaion Journal of Inequaliie and Applicaion Volume 2010, Aricle ID 960365, 6 page doi:10.1155/2010/960365 Reearch Aricle An Upper Bound on he Criical Value Involved in he Blaiu Problem

More information

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm Augmening Pah Algorihm Greedy-algorihm: ar wih f (e) = everywhere find an - pah wih f (e) < c(e) on every edge augmen flow along he pah repea a long a poible The Reidual Graph From he graph G = (V, E,

More information

Please Complete Course Survey. CMPSCI 311: Introduction to Algorithms. Approximation Algorithms. Coping With NP-Completeness. Greedy Vertex Cover

Please Complete Course Survey. CMPSCI 311: Introduction to Algorithms. Approximation Algorithms. Coping With NP-Completeness. Greedy Vertex Cover Pleae Complee Coure Survey CMPSCI : Inroducion o Algorihm Dealing wih NP-Compleene Dan Sheldon hp: //owl.oi.uma.edu/parner/coureevalsurvey/uma/ Univeriy of Maachue Slide Adaped from Kevin Wayne La Compiled:

More information

20. Applications of the Genetic-Drift Model

20. Applications of the Genetic-Drift Model 0. Applicaions of he Geneic-Drif Model 1) Deermining he probabiliy of forming any paricular combinaion of genoypes in he nex generaion: Example: If he parenal allele frequencies are p 0 = 0.35 and q 0

More information

Solutions for Assignment 2

Solutions for Assignment 2 Faculy of rs and Science Universiy of Torono CSC 358 - Inroducion o Compuer Neworks, Winer 218 Soluions for ssignmen 2 Quesion 1 (2 Poins): Go-ack n RQ In his quesion, we review how Go-ack n RQ can be

More information

EECS 141: FALL 00 MIDTERM 2

EECS 141: FALL 00 MIDTERM 2 Universiy of California College of Engineering Deparmen of Elecrical Engineering and Compuer Science J. M. Rabaey TuTh9:30-11am ee141@eecs EECS 141: FALL 00 MIDTERM 2 For all problems, you can assume he

More information

u(t) Figure 1. Open loop control system

u(t) Figure 1. Open loop control system Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference

More information