Perhaps the method will give that for every e > U f() > p - 3/+e There is o o-trivial upper boud for f() ad ot eve f() < Z - e. seems to be kow, where

Size: px
Start display at page:

Download "Perhaps the method will give that for every e > U f() > p - 3/+e There is o o-trivial upper boud for f() ad ot eve f() < Z - e. seems to be kow, where"

Transcription

1 ON MAXIMUM CHORDAL SUBGRAPH * Paul Erdos Mathematical Istitute of the Hugaria Academy of Scieces ad Reu Laskar Clemso Uiversity 1. Let G() deote a udirected graph, with vertices ad V(G) deote the vertex set, E(G) deote the edge set. Let e(g) deote the umber of edges of G. It wí11 be assumed that G() has o loops or multiple edges. A graph G() is chordal (triagulated, rigid circuit) if every cycle of legth > 3 has a chord : amely a edge joiig two ocosecutive vertices o the cycle. The class of chordal graph iclude trees, k-trees, complete graphs ad iterval graphs. Chordal graphs have applicatio i facility locatio [], schedulig problems [8], ad i the solutio of sparse systems of liear equatio 110]. Such graphs are also kow to be perfect. Certai problems that are kow to be NP-hard for geeral graphs ca be solved i polyomial time for chordal graphs [6]. As a result, chordal graphs have bee studied by may, e.g. [1], (5]. If a graph is ot chordal, the followig questios are quite appropriate to ask : 1) What is the miimal set of ew edges to be added to the graph to make it chordal? ) What is the miimal set of edges to be deleted from the graph such that the resultig graph is a maximum chordal subgraph? Rose, Tarja ad Lueker have aswered 1) algorithmically [9]. I aswer to ) recetly Dearig, Shier, ad Warer [3] have developed a polyomial algorithm to geerate a maximal chordal subgraph. It may be poited out that their algorithm does ot geerate a maximum chordal subgraph. I aswer to 1) Erdos [4] showed that for some positive e > 0 f() > z - -c t This paper is i fial form ad will ot appear elsewhere. CONGRESSUS NUMERANTIUM, VOL. 39 (1983), pp

2 Perhaps the method will give that for every e > U f() > p - 3/+e There is o o-trivial upper boud for f() ad ot eve f() < Z - e. seems to be kow, where f() is the smallest iteger so that for every graph with vertices oe ca add <_ f() ew edges so that the resultig graph would be chordal. This ote determies asymptotically the miimum umber of edges to be deleted from the graph such that the resultig graph is a maximum chordal subgraph.. Deote by f() the smallest iteger such that every graph G() with vertices ca be made chordal be deletig <- f() edges of G(). Theorem 1. f() <- - ( 1+o(l»V 31 ~, where o(1) ' o as 1 Proof : Let T(,t) be the Tura graph [111, i.e. a complete t-partite graph with vertices with approximately vertices i each color t class. Let v l, y,.., v t deote the color classes. The umber of edges of T(,t) e(t,(,t)) CZ) - t Z (1-1) (1) Let G 1 be a spaig chordal subgraph of T(,t) havig maximum umber of edges. Clearly G 1 caot cotai ay cycle whose vertices are i t o differet color classes. Thus, the iduced subgraph of ay two color classes of G 1 must be a tree. Hece, e(g 1 ) ( t)( - 1) (-') 368

3 Let H be a spaig subgraph of T(,t) descríbrd as 1)elow : Cosider xí e l' í,. joi each k t : {x 1' x '.. ' x t ), xx to all vertices of V., i 4 j, j=1,,.., Clearly H is chordal beig a split graph 17). Also e(h) - ( Z)( - 1). Thus by () H is a spaig chordal subgraph of T(,t) of maximum size. The umber of edges to be deleted from T(,t) to obtai H is (1-t) - ()( t 1) t _ t++ t t Now take t =. The (3) becomes - ( 1+o(1))V ~~` where o(1) - 0 as ~ -. Thus, f(), - ( l+o(1)i 3/ Theorem. / f() < - (1 - e) 3 for every e > 0 if > 0 (e). Proof : We ca assume that G() has at least - (1 - e)d_^ 3/ edges. Suppose G() has () - e l edges ad that the largest chordal subgraph of G() has e edges. It suffices to prove e 3/ (1 - e) (4) Let rj > 0 be small, much smaller tha e. he costruct a subgraph G(m) cosistig of m vertices each of which has degree > (1-q). The co structío is as follows : delete from G() a vertex x l (if ay) of degree 5 (1-) ad cotiue this process as log as possible. Suppose after k such steps we obtai G(m) = G(x l`+1, x K+,.., x ) each vertex of which has degree > (1-). Claim k c C (5) t. 369

4 s., here C E depeds o E ad ad ot o. To prove the claim observe that if k = [C J] e(g()) < ( m) + k(l (-k) + k(1 - f) (6) + k - rlk 3/ ( - if CE is sufficietly large. Thus by (4) we have othig to prove, Cosider G(m). Assume that t is the largest positive iteger such that G(m) cotais a K t. The by Tura's theorem G(m) has at most M (1 - t) edges (7) Let Kt = (y l, y ' " ' yt). Now deg G(m) y i > (1-), for each i, i=1,,.., t. Adjoi all the edges joiig to each y to vertices outside of i K t. This produces a chordal subgraph with at least t((l-) - (t-1)) edges t(1-) - (8) Now if t = [4v], the (8) becomes 411 3/ (l-) - 16 which is 3/ / Thus, we get a chordal subgraph k,hose umber of edges > (9) This proves (4). Thus t < 4ti '1Q1 370

5 Now from (7) ad (8) ` el + e > mt t(1-) t > t t(1-) 16 (-k) t + t(1-) - 16 t t + t + t(1-q) 16 3/ C e, t + t(1-) - 16 (1-E),/- 3/ sice to + t is miimum if t = ad other terms ca be absorbed ito e 3/ Thus combiig theorems 1 ad we ca state Theorem 3. f() = - (1 + 0(1)) 3/. Perhaps the followig problem is of some iterest ad deserves some study. Let f( ;t) be the smallest iteger for which every G( ;f( ;t)) cotais a chordal subgraph of t edges. At the momet we oly kow that f(,) _ [4] + 1 (11) We do ot give the details of the proof of (11) but oly idicate some of the ecessary steps. We hope to retur to this problem i the future. Observe that the complete bipartite graph of white ad +1 black vertices immediately shot: that f(,)? 4. To prove the upper boud i (11) we oly remark that this immediately follows if our G(,[, ]+1) is assumed to be coected. For the by Tura's theorem our graph cotais a triagle ad by a simple argumet this triagle ca be exteded to a chordal graph of edges. If the graph is ot coected somewhat more 37 1

6 complicated methods are eeded, which as we stated we hope to discuss at aother occasio. Just oe more remark. It is well kow that every z graph of G( ;[ 4 ]+1) cotais a edge (x,,x ) ad o further vertices x i joied to both x l ad x. This implies i fact that f(,(l + t)) _ [4 ] + 1 for sufficietly small E > 0. Ackowledgemet The secod author thakfully ackowledges the partial support from the Natioal Sciece Foudatio Grat #ISP (EPSCoR) to do this research. 37

7 Refereces 1. P. Buema, "A characterizatio of rigid circuit graphs." Discrete "fathematícs, 9 (1974) R. Chadrasekara ad A. Tamir, "Polymoially bouded algorithms for locatig p-ceters o a tree." Discussio paper No. 358, Ceter for Mathematical Studies i Ecoomics ad Maagemet Sciece, -Northwester Uiversity, (1978). 3. P. M. Dearig, D. R. Shier, D. D. Warer, "Maximal Chordal Subgraphs." Clemso Uiversity Techical) Report ;'404, December P. Erdos, "Some ew applicatios of probability methods to combiatorial aalysis ad graph theory." Proc. 5th S. E. Cof. Combiatorics, Graph Theory, ad Computig, D. R. Fulkerso ad 0. A. Gross, "Icidece matrices ad iterval graphs." Pacific J. Math, 15 (1965) F. Gavril, "Algorithms for miimum collorig, maximum clique, miimum coverig by cliques, ad maximum idepedet set of chordal graph," SIAM J. Comput., 1 (197) M. Golumbic, "Algorithmic Graph Theory ad Perfect Graphs." Academic Press New York, (1980). 8 C. Papedimitrio ad M. Yaakakis, "Schedulig iterval-ordered tasks." SIAM J. Comput., 8 (1979) D. Rose, R. Tarja ad G. Lueker, "Algorithmic aspects of vertex elimiatio o graphs." SIAM J. Comput., 5 (1976) D. Rose, "A graph-theoretic study of the umerical solutio of sparse positive defiite systems of liear equatios." (R. Read, ed.), Graph Theory ad Computig, Academic Press, New York, (197) P. Tura, "O a extremal problem i graph theory." (I Hugaria), Mat. Fiz. Lapok, 48 (1941)

On (K t e)-saturated Graphs

On (K t e)-saturated Graphs Noame mauscript No. (will be iserted by the editor O (K t e-saturated Graphs Jessica Fuller Roald J. Gould the date of receipt ad acceptace should be iserted later Abstract Give a graph H, we say a graph

More information

Strong Complementary Acyclic Domination of a Graph

Strong Complementary Acyclic Domination of a Graph Aals of Pure ad Applied Mathematics Vol 8, No, 04, 83-89 ISSN: 79-087X (P), 79-0888(olie) Published o 7 December 04 wwwresearchmathsciorg Aals of Strog Complemetary Acyclic Domiatio of a Graph NSaradha

More information

Counting the Number of Minimum Roman Dominating Functions of a Graph

Counting the Number of Minimum Roman Dominating Functions of a Graph Coutig the Number of Miimum Roma Domiatig Fuctios of a Graph SHI ZHENG ad KOH KHEE MENG, Natioal Uiversity of Sigapore We provide two algorithms coutig the umber of miimum Roma domiatig fuctios of a graph

More information

1 Graph Sparsfication

1 Graph Sparsfication CME 305: Discrete Mathematics ad Algorithms 1 Graph Sparsficatio I this sectio we discuss the approximatio of a graph G(V, E) by a sparse graph H(V, F ) o the same vertex set. I particular, we cosider

More information

The isoperimetric problem on the hypercube

The isoperimetric problem on the hypercube The isoperimetric problem o the hypercube Prepared by: Steve Butler November 2, 2005 1 The isoperimetric problem We will cosider the -dimesioal hypercube Q Recall that the hypercube Q is a graph whose

More information

Combination Labelings Of Graphs

Combination Labelings Of Graphs Applied Mathematics E-Notes, (0), - c ISSN 0-0 Available free at mirror sites of http://wwwmaththuedutw/ame/ Combiatio Labeligs Of Graphs Pak Chig Li y Received February 0 Abstract Suppose G = (V; E) is

More information

Sum-connectivity indices of trees and unicyclic graphs of fixed maximum degree

Sum-connectivity indices of trees and unicyclic graphs of fixed maximum degree 1 Sum-coectivity idices of trees ad uicyclic graphs of fixed maximum degree Zhibi Du a, Bo Zhou a *, Nead Triajstić b a Departmet of Mathematics, South Chia Normal Uiversity, uagzhou 510631, Chia email:

More information

Module 8-7: Pascal s Triangle and the Binomial Theorem

Module 8-7: Pascal s Triangle and the Binomial Theorem Module 8-7: Pascal s Triagle ad the Biomial Theorem Gregory V. Bard April 5, 017 A Note about Notatio Just to recall, all of the followig mea the same thig: ( 7 7C 4 C4 7 7C4 5 4 ad they are (all proouced

More information

A RELATIONSHIP BETWEEN BOUNDS ON THE SUM OF SQUARES OF DEGREES OF A GRAPH

A RELATIONSHIP BETWEEN BOUNDS ON THE SUM OF SQUARES OF DEGREES OF A GRAPH J. Appl. Math. & Computig Vol. 21(2006), No. 1-2, pp. 233-238 Website: http://jamc.et A RELATIONSHIP BETWEEN BOUNDS ON THE SUM OF SQUARES OF DEGREES OF A GRAPH YEON SOO YOON AND JU KYUNG KIM Abstract.

More information

Matrix Partitions of Split Graphs

Matrix Partitions of Split Graphs Matrix Partitios of Split Graphs Tomás Feder, Pavol Hell, Ore Shklarsky Abstract arxiv:1306.1967v2 [cs.dm] 20 Ju 2013 Matrix partitio problems geeralize a umber of atural graph partitio problems, ad have

More information

Lecture 5. Counting Sort / Radix Sort

Lecture 5. Counting Sort / Radix Sort Lecture 5. Coutig Sort / Radix Sort T. H. Corme, C. E. Leiserso ad R. L. Rivest Itroductio to Algorithms, 3rd Editio, MIT Press, 2009 Sugkyukwa Uiversity Hyuseug Choo choo@skku.edu Copyright 2000-2018

More information

2 X = 2 X. The number of all permutations of a set X with n elements is. n! = n (n 1) (n 2) nn e n

2 X = 2 X. The number of all permutations of a set X with n elements is. n! = n (n 1) (n 2) nn e n 1 Discrete Mathematics revisited. Facts to remember Give set X, the umber of subsets of X is give by X = X. The umber of all permutatios of a set X with elemets is! = ( 1) ( )... 1 e π. The umber ( ) k

More information

THE COMPETITION NUMBERS OF JOHNSON GRAPHS

THE COMPETITION NUMBERS OF JOHNSON GRAPHS Discussioes Mathematicae Graph Theory 30 (2010 ) 449 459 THE COMPETITION NUMBERS OF JOHNSON GRAPHS Suh-Ryug Kim, Boram Park Departmet of Mathematics Educatio Seoul Natioal Uiversity, Seoul 151 742, Korea

More information

An Efficient Algorithm for Graph Bisection of Triangularizations

An Efficient Algorithm for Graph Bisection of Triangularizations A Efficiet Algorithm for Graph Bisectio of Triagularizatios Gerold Jäger Departmet of Computer Sciece Washigto Uiversity Campus Box 1045 Oe Brookigs Drive St. Louis, Missouri 63130-4899, USA jaegerg@cse.wustl.edu

More information

Random Graphs and Complex Networks T

Random Graphs and Complex Networks T Radom Graphs ad Complex Networks T-79.7003 Charalampos E. Tsourakakis Aalto Uiversity Lecture 3 7 September 013 Aoucemet Homework 1 is out, due i two weeks from ow. Exercises: Probabilistic iequalities

More information

An Efficient Algorithm for Graph Bisection of Triangularizations

An Efficient Algorithm for Graph Bisection of Triangularizations Applied Mathematical Scieces, Vol. 1, 2007, o. 25, 1203-1215 A Efficiet Algorithm for Graph Bisectio of Triagularizatios Gerold Jäger Departmet of Computer Sciece Washigto Uiversity Campus Box 1045, Oe

More information

New Results on Energy of Graphs of Small Order

New Results on Energy of Graphs of Small Order Global Joural of Pure ad Applied Mathematics. ISSN 0973-1768 Volume 13, Number 7 (2017), pp. 2837-2848 Research Idia Publicatios http://www.ripublicatio.com New Results o Eergy of Graphs of Small Order

More information

Ones Assignment Method for Solving Traveling Salesman Problem

Ones Assignment Method for Solving Traveling Salesman Problem Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:

More information

A study on Interior Domination in Graphs

A study on Interior Domination in Graphs IOSR Joural of Mathematics (IOSR-JM) e-issn: 2278-5728, p-issn: 219-765X. Volume 12, Issue 2 Ver. VI (Mar. - Apr. 2016), PP 55-59 www.iosrjourals.org A study o Iterior Domiatio i Graphs A. Ato Kisley 1,

More information

Graphs. Minimum Spanning Trees. Slides by Rose Hoberman (CMU)

Graphs. Minimum Spanning Trees. Slides by Rose Hoberman (CMU) Graphs Miimum Spaig Trees Slides by Rose Hoberma (CMU) Problem: Layig Telephoe Wire Cetral office 2 Wirig: Naïve Approach Cetral office Expesive! 3 Wirig: Better Approach Cetral office Miimize the total

More information

Some cycle and path related strongly -graphs

Some cycle and path related strongly -graphs Some cycle ad path related strogly -graphs I. I. Jadav, G. V. Ghodasara Research Scholar, R. K. Uiversity, Rajkot, Idia. H. & H. B. Kotak Istitute of Sciece,Rajkot, Idia. jadaviram@gmail.com gaurag ejoy@yahoo.co.i

More information

6.854J / J Advanced Algorithms Fall 2008

6.854J / J Advanced Algorithms Fall 2008 MIT OpeCourseWare http://ocw.mit.edu 6.854J / 18.415J Advaced Algorithms Fall 2008 For iformatio about citig these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 18.415/6.854 Advaced Algorithms

More information

Computational Geometry

Computational Geometry Computatioal Geometry Chapter 4 Liear programmig Duality Smallest eclosig disk O the Ageda Liear Programmig Slides courtesy of Craig Gotsma 4. 4. Liear Programmig - Example Defie: (amout amout cosumed

More information

Super Vertex Magic and E-Super Vertex Magic. Total Labelling

Super Vertex Magic and E-Super Vertex Magic. Total Labelling Proceedigs of the Iteratioal Coferece o Applied Mathematics ad Theoretical Computer Sciece - 03 6 Super Vertex Magic ad E-Super Vertex Magic Total Labellig C.J. Deei ad D. Atoy Xavier Abstract--- For a

More information

Protected points in ordered trees

Protected points in ordered trees Applied Mathematics Letters 008 56 50 www.elsevier.com/locate/aml Protected poits i ordered trees Gi-Sag Cheo a, Louis W. Shapiro b, a Departmet of Mathematics, Sugkyukwa Uiversity, Suwo 440-746, Republic

More information

Planar graphs. Definition. A graph is planar if it can be drawn on the plane in such a way that no two edges cross each other.

Planar graphs. Definition. A graph is planar if it can be drawn on the plane in such a way that no two edges cross each other. Plaar graphs Defiitio. A graph is plaar if it ca be draw o the plae i such a way that o two edges cross each other. Example: Face 1 Face 2 Exercise: Which of the followig graphs are plaar? K, P, C, K,m,

More information

A Note on Chromatic Transversal Weak Domination in Graphs

A Note on Chromatic Transversal Weak Domination in Graphs Iteratioal Joural of Mathematics Treds ad Techology Volume 17 Number 2 Ja 2015 A Note o Chromatic Trasversal Weak Domiatio i Graphs S Balamuruga 1, P Selvalakshmi 2 ad A Arivalaga 1 Assistat Professor,

More information

MAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS

MAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS Fura Uiversity Electroic Joural of Udergraduate Matheatics Volue 00, 1996 6-16 MAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS DAVID SITTON Abstract. How ay edges ca there be i a axiu atchig i a coplete

More information

ON A PROBLEM OF C. E. SHANNON IN GRAPH THEORY

ON A PROBLEM OF C. E. SHANNON IN GRAPH THEORY ON A PROBLEM OF C. E. SHANNON IN GRAPH THEORY m. rosefeld1 1. Itroductio. We cosider i this paper oly fiite odirected graphs without multiple edges ad we assume that o each vertex of the graph there is

More information

INTERSECTION CORDIAL LABELING OF GRAPHS

INTERSECTION CORDIAL LABELING OF GRAPHS INTERSECTION CORDIAL LABELING OF GRAPHS G Meea, K Nagaraja Departmet of Mathematics, PSR Egieerig College, Sivakasi- 66 4, Virudhuagar(Dist) Tamil Nadu, INDIA meeag9@yahoocoi Departmet of Mathematics,

More information

Project 2.5 Improved Euler Implementation

Project 2.5 Improved Euler Implementation Project 2.5 Improved Euler Implemetatio Figure 2.5.10 i the text lists TI-85 ad BASIC programs implemetig the improved Euler method to approximate the solutio of the iitial value problem dy dx = x+ y,

More information

Lecturers: Sanjam Garg and Prasad Raghavendra Feb 21, Midterm 1 Solutions

Lecturers: Sanjam Garg and Prasad Raghavendra Feb 21, Midterm 1 Solutions U.C. Berkeley CS170 : Algorithms Midterm 1 Solutios Lecturers: Sajam Garg ad Prasad Raghavedra Feb 1, 017 Midterm 1 Solutios 1. (4 poits) For the directed graph below, fid all the strogly coected compoets

More information

condition w i B i S maximum u i

condition w i B i S maximum u i ecture 10 Dyamic Programmig 10.1 Kapsack Problem November 1, 2004 ecturer: Kamal Jai Notes: Tobias Holgers We are give a set of items U = {a 1, a 2,..., a }. Each item has a weight w i Z + ad a utility

More information

The Closest Line to a Data Set in the Plane. David Gurney Southeastern Louisiana University Hammond, Louisiana

The Closest Line to a Data Set in the Plane. David Gurney Southeastern Louisiana University Hammond, Louisiana The Closest Lie to a Data Set i the Plae David Gurey Southeaster Louisiaa Uiversity Hammod, Louisiaa ABSTRACT This paper looks at three differet measures of distace betwee a lie ad a data set i the plae:

More information

The Adjacency Matrix and The nth Eigenvalue

The Adjacency Matrix and The nth Eigenvalue Spectral Graph Theory Lecture 3 The Adjacecy Matrix ad The th Eigevalue Daiel A. Spielma September 5, 2012 3.1 About these otes These otes are ot ecessarily a accurate represetatio of what happeed i class.

More information

Average Connectivity and Average Edge-connectivity in Graphs

Average Connectivity and Average Edge-connectivity in Graphs Average Coectivity ad Average Edge-coectivity i Graphs Jaehoo Kim, Suil O July 1, 01 Abstract Coectivity ad edge-coectivity of a graph measure the difficulty of breakig the graph apart, but they are very

More information

On Infinite Groups that are Isomorphic to its Proper Infinite Subgroup. Jaymar Talledo Balihon. Abstract

On Infinite Groups that are Isomorphic to its Proper Infinite Subgroup. Jaymar Talledo Balihon. Abstract O Ifiite Groups that are Isomorphic to its Proper Ifiite Subgroup Jaymar Talledo Baliho Abstract Two groups are isomorphic if there exists a isomorphism betwee them Lagrage Theorem states that the order

More information

Lecture 2: Spectra of Graphs

Lecture 2: Spectra of Graphs Spectral Graph Theory ad Applicatios WS 20/202 Lecture 2: Spectra of Graphs Lecturer: Thomas Sauerwald & He Su Our goal is to use the properties of the adjacecy/laplacia matrix of graphs to first uderstad

More information

The Eigen-Cover Ratio of a Graph: Asymptotes, Domination and Areas

The Eigen-Cover Ratio of a Graph: Asymptotes, Domination and Areas The ige-cover Ratio of a Graph: Asymptotes, Domiatio ad Areas Paul August Witer ad Carol Lye Jessop Mathematics, UKZN, Durba, outh Africa-email: witerp@ukzacza Abstract The separate study of the two cocepts

More information

Improved Random Graph Isomorphism

Improved Random Graph Isomorphism Improved Radom Graph Isomorphism Tomek Czajka Gopal Paduraga Abstract Caoical labelig of a graph cosists of assigig a uique label to each vertex such that the labels are ivariat uder isomorphism. Such

More information

9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence

9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence _9.qxd // : AM Page Chapter 9 Sequeces, Series, ad Probability 9. Sequeces ad Series What you should lear Use sequece otatio to write the terms of sequeces. Use factorial otatio. Use summatio otatio to

More information

n n B. How many subsets of C are there of cardinality n. We are selecting elements for such a

n n B. How many subsets of C are there of cardinality n. We are selecting elements for such a 4. [10] Usig a combiatorial argumet, prove that for 1: = 0 = Let A ad B be disjoit sets of cardiality each ad C = A B. How may subsets of C are there of cardiality. We are selectig elemets for such a subset

More information

Fuzzy Minimal Solution of Dual Fully Fuzzy Matrix Equations

Fuzzy Minimal Solution of Dual Fully Fuzzy Matrix Equations Iteratioal Coferece o Applied Mathematics, Simulatio ad Modellig (AMSM 2016) Fuzzy Miimal Solutio of Dual Fully Fuzzy Matrix Equatios Dequa Shag1 ad Xiaobi Guo2,* 1 Sciece Courses eachig Departmet, Gasu

More information

Alpha Individual Solutions MAΘ National Convention 2013

Alpha Individual Solutions MAΘ National Convention 2013 Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5

More information

Lecture 1: Introduction and Strassen s Algorithm

Lecture 1: Introduction and Strassen s Algorithm 5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access

More information

15-859E: Advanced Algorithms CMU, Spring 2015 Lecture #2: Randomized MST and MST Verification January 14, 2015

15-859E: Advanced Algorithms CMU, Spring 2015 Lecture #2: Randomized MST and MST Verification January 14, 2015 15-859E: Advaced Algorithms CMU, Sprig 2015 Lecture #2: Radomized MST ad MST Verificatio Jauary 14, 2015 Lecturer: Aupam Gupta Scribe: Yu Zhao 1 Prelimiaries I this lecture we are talkig about two cotets:

More information

Syddansk Universitet. The total irregularity of a graph. Abdo, H.; Brandt, S.; Dimitrov, D.

Syddansk Universitet. The total irregularity of a graph. Abdo, H.; Brandt, S.; Dimitrov, D. Syddask Uiversitet The total irregularity of a graph Abdo, H.; Bradt, S.; Dimitrov, D. Published i: Discrete Mathematics & Theoretical Computer Sciece Publicatio date: 014 Documet versio Publisher's PDF,

More information

CHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs

CHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs CHAPTER IV: GRAPH THEORY Sectio : Itroductio to Graphs Sice this class is called Number-Theoretic ad Discrete Structures, it would be a crime to oly focus o umber theory regardless how woderful those topics

More information

Monochromatic Structures in Edge-coloured Graphs and Hypergraphs - A survey

Monochromatic Structures in Edge-coloured Graphs and Hypergraphs - A survey Moochromatic Structures i Edge-coloured Graphs ad Hypergraphs - A survey Shiya Fujita 1, Hery Liu 2, ad Colto Magat 3 1 Iteratioal College of Arts ad Scieces Yokohama City Uiversity 22-2, Seto, Kaazawa-ku

More information

Thompson s Group F (p + 1) is not Minimally Almost Convex

Thompson s Group F (p + 1) is not Minimally Almost Convex Thompso s Group F (p + ) is ot Miimally Almost Covex Claire Wladis Thompso s Group F (p + ). A Descriptio of F (p + ) Thompso s group F (p + ) ca be defied as the group of piecewiseliear orietatio-preservig

More information

Minimum Spanning Trees

Minimum Spanning Trees Presetatio for use with the textbook, lgorithm esig ad pplicatios, by M. T. Goodrich ad R. Tamassia, Wiley, 0 Miimum Spaig Trees 0 Goodrich ad Tamassia Miimum Spaig Trees pplicatio: oectig a Network Suppose

More information

3D Model Retrieval Method Based on Sample Prediction

3D Model Retrieval Method Based on Sample Prediction 20 Iteratioal Coferece o Computer Commuicatio ad Maagemet Proc.of CSIT vol.5 (20) (20) IACSIT Press, Sigapore 3D Model Retrieval Method Based o Sample Predictio Qigche Zhag, Ya Tag* School of Computer

More information

Minimum Spanning Trees. Application: Connecting a Network

Minimum Spanning Trees. Application: Connecting a Network Miimum Spaig Tree // : Presetatio for use with the textbook, lgorithm esig ad pplicatios, by M. T. oodrich ad R. Tamassia, Wiley, Miimum Spaig Trees oodrich ad Tamassia Miimum Spaig Trees pplicatio: oectig

More information

Some New Results on Prime Graphs

Some New Results on Prime Graphs Ope Joural of Discrete Mathematics, 202, 2, 99-04 http://dxdoiorg/0426/ojdm202209 Published Olie July 202 (http://wwwscirporg/joural/ojdm) Some New Results o Prime Graphs Samir Vaidya, Udaya M Prajapati

More information

Spanning Maximal Planar Subgraphs of Random Graphs

Spanning Maximal Planar Subgraphs of Random Graphs Spaig Maximal Plaar Subgraphs of Radom Graphs 6. Bollobiis* Departmet of Mathematics, Louisiaa State Uiversity, Bato Rouge, LA 70803 A. M. Frieze? Departmet of Mathematics, Caregie-Mello Uiversity, Pittsburgh,

More information

Some non-existence results on Leech trees

Some non-existence results on Leech trees Some o-existece results o Leech trees László A.Székely Hua Wag Yog Zhag Uiversity of South Carolia This paper is dedicated to the memory of Domiique de Cae, who itroduced LAS to Leech trees.. Abstract

More information

Computer Science Foundation Exam. August 12, Computer Science. Section 1A. No Calculators! KEY. Solutions and Grading Criteria.

Computer Science Foundation Exam. August 12, Computer Science. Section 1A. No Calculators! KEY. Solutions and Grading Criteria. Computer Sciece Foudatio Exam August, 005 Computer Sciece Sectio A No Calculators! Name: SSN: KEY Solutios ad Gradig Criteria Score: 50 I this sectio of the exam, there are four (4) problems. You must

More information

Characterizing graphs of maximum principal ratio

Characterizing graphs of maximum principal ratio Characterizig graphs of maximum pricipal ratio Michael Tait ad Josh Tobi November 9, 05 Abstract The pricipal ratio of a coected graph, deoted γg, is the ratio of the maximum ad miimum etries of its first

More information

Lecture Notes on Integer Linear Programming

Lecture Notes on Integer Linear Programming Lecture Notes o Iteger Liear Programmig Roel va de Broek October 15, 2018 These otes supplemet the material o (iteger) liear programmig covered by the lectures i the course Algorithms for Decisio Support.

More information

ON THE DEFINITION OF A CLOSE-TO-CONVEX FUNCTION

ON THE DEFINITION OF A CLOSE-TO-CONVEX FUNCTION I terat. J. Mh. & Math. Sci. Vol. (1978) 125-132 125 ON THE DEFINITION OF A CLOSE-TO-CONVEX FUNCTION A. W. GOODMAN ad E. B. SAFF* Mathematics Dept, Uiversity of South Florida Tampa, Florida 33620 Dedicated

More information

MINIMUM CROSSINGS IN JOIN OF GRAPHS WITH PATHS AND CYCLES

MINIMUM CROSSINGS IN JOIN OF GRAPHS WITH PATHS AND CYCLES 3 Acta Electrotechica et Iformatica, Vol. 1, No. 3, 01, 3 37, DOI: 10.478/v10198-01-008-0 MINIMUM CROSSINGS IN JOIN OF GRAPHS WITH PATHS AND CYCLES Mariá KLEŠČ, Matúš VALO Departmet of Mathematics ad Theoretical

More information

Analysis of Algorithms

Analysis of Algorithms Aalysis of Algorithms Ruig Time of a algorithm Ruig Time Upper Bouds Lower Bouds Examples Mathematical facts Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite

More information

Examples and Applications of Binary Search

Examples and Applications of Binary Search Toy Gog ITEE Uiersity of Queeslad I the secod lecture last week we studied the biary search algorithm that soles the problem of determiig if a particular alue appears i a sorted list of iteger or ot. We

More information

Convergence results for conditional expectations

Convergence results for conditional expectations Beroulli 11(4), 2005, 737 745 Covergece results for coditioal expectatios IRENE CRIMALDI 1 ad LUCA PRATELLI 2 1 Departmet of Mathematics, Uiversity of Bologa, Piazza di Porta Sa Doato 5, 40126 Bologa,

More information

On Alliance Partitions and Bisection Width for Planar Graphs

On Alliance Partitions and Bisection Width for Planar Graphs Joural of Graph Algorithms ad Applicatios http://jgaa.ifo/ vol. 17, o. 6, pp. 599 614 (013) DOI: 10.7155/jgaa.00307 O Alliace Partitios ad Bisectio Width for Plaar Graphs Marti Olse 1 Morte Revsbæk 1 AU

More information

Pseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance

Pseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Pseudocode ( 1.1) High-level descriptio of a algorithm More structured

More information

. Written in factored form it is easy to see that the roots are 2, 2, i,

. Written in factored form it is easy to see that the roots are 2, 2, i, CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or

More information

Outline and Reading. Analysis of Algorithms. Running Time. Experimental Studies. Limitations of Experiments. Theoretical Analysis

Outline and Reading. Analysis of Algorithms. Running Time. Experimental Studies. Limitations of Experiments. Theoretical Analysis Outlie ad Readig Aalysis of Algorithms Iput Algorithm Output Ruig time ( 3.) Pseudo-code ( 3.2) Coutig primitive operatios ( 3.3-3.) Asymptotic otatio ( 3.6) Asymptotic aalysis ( 3.7) Case study Aalysis

More information

Octahedral Graph Scaling

Octahedral Graph Scaling Octahedral Graph Scalig Peter Russell Jauary 1, 2015 Abstract There is presetly o strog iterpretatio for the otio of -vertex graph scalig. This paper presets a ew defiitio for the term i the cotext of

More information

University of Waterloo Department of Electrical and Computer Engineering ECE 250 Algorithms and Data Structures

University of Waterloo Department of Electrical and Computer Engineering ECE 250 Algorithms and Data Structures Uiversity of Waterloo Departmet of Electrical ad Computer Egieerig ECE 250 Algorithms ad Data Structures Midterm Examiatio ( pages) Istructor: Douglas Harder February 7, 2004 7:30-9:00 Name (last, first)

More information

BOOLEAN MATHEMATICS: GENERAL THEORY

BOOLEAN MATHEMATICS: GENERAL THEORY CHAPTER 3 BOOLEAN MATHEMATICS: GENERAL THEORY 3.1 ISOMORPHIC PROPERTIES The ame Boolea Arithmetic was chose because it was discovered that literal Boolea Algebra could have a isomorphic umerical aspect.

More information

Cubic Polynomial Curves with a Shape Parameter

Cubic Polynomial Curves with a Shape Parameter roceedigs of the th WSEAS Iteratioal Coferece o Robotics Cotrol ad Maufacturig Techology Hagzhou Chia April -8 00 (pp5-70) Cubic olyomial Curves with a Shape arameter MO GUOLIANG ZHAO YANAN Iformatio ad

More information

BASED ON ITERATIVE ERROR-CORRECTION

BASED ON ITERATIVE ERROR-CORRECTION A COHPARISO OF CRYPTAALYTIC PRICIPLES BASED O ITERATIVE ERROR-CORRECTIO Miodrag J. MihaljeviC ad Jova Dj. GoliC Istitute of Applied Mathematics ad Electroics. Belgrade School of Electrical Egieerig. Uiversity

More information

4-PRIME CORDIAL LABELING OF SOME DEGREE SPLITTING GRAPHS

4-PRIME CORDIAL LABELING OF SOME DEGREE SPLITTING GRAPHS Iteratioal Joural of Maagemet, IT & Egieerig Vol. 8 Issue 7, July 018, ISSN: 49-0558 Impact Factor: 7.119 Joural Homepage: Double-Blid Peer Reviewed Refereed Ope Access Iteratioal Joural - Icluded i the

More information

c-dominating Sets for Families of Graphs

c-dominating Sets for Families of Graphs c-domiatig Sets for Families of Graphs Kelsie Syder Mathematics Uiversity of Mary Washigto April 6, 011 1 Abstract The topic of domiatio i graphs has a rich history, begiig with chess ethusiasts i the

More information

Mean cordiality of some snake graphs

Mean cordiality of some snake graphs Palestie Joural of Mathematics Vol. 4() (015), 49 445 Palestie Polytechic Uiversity-PPU 015 Mea cordiality of some sake graphs R. Poraj ad S. Sathish Narayaa Commuicated by Ayma Badawi MSC 010 Classificatios:

More information

Asymptotics of Pattern Avoidance in the Klazar Set Partition and Permutation-Tuple Settings Permutation Patterns 2017 Abstract

Asymptotics of Pattern Avoidance in the Klazar Set Partition and Permutation-Tuple Settings Permutation Patterns 2017 Abstract Asymptotics of Patter Avoiace i the Klazar Set Partitio a Permutatio-Tuple Settigs Permutatio Patters 2017 Abstract Bejami Guby Departmet of Mathematics Harvar Uiversity Cambrige, Massachusetts, U.S.A.

More information

Lecture 6. Lecturer: Ronitt Rubinfeld Scribes: Chen Ziv, Eliav Buchnik, Ophir Arie, Jonathan Gradstein

Lecture 6. Lecturer: Ronitt Rubinfeld Scribes: Chen Ziv, Eliav Buchnik, Ophir Arie, Jonathan Gradstein 068.670 Subliear Time Algorithms November, 0 Lecture 6 Lecturer: Roitt Rubifeld Scribes: Che Ziv, Eliav Buchik, Ophir Arie, Joatha Gradstei Lesso overview. Usig the oracle reductio framework for approximatig

More information

Relationship between augmented eccentric connectivity index and some other graph invariants

Relationship between augmented eccentric connectivity index and some other graph invariants Iteratioal Joural of Advaced Mathematical Scieces, () (03) 6-3 Sciece Publishig Corporatio wwwsciecepubcocom/idexphp/ijams Relatioship betwee augmeted eccetric coectivity idex ad some other graph ivariats

More information

A NOTE ON COARSE GRAINED PARALLEL INTEGER SORTING

A NOTE ON COARSE GRAINED PARALLEL INTEGER SORTING Chater 26 A NOTE ON COARSE GRAINED PARALLEL INTEGER SORTING A. Cha ad F. Dehe School of Comuter Sciece Carleto Uiversity Ottawa, Caada K1S 5B6 æ {acha,dehe}@scs.carleto.ca Abstract Keywords: We observe

More information

Bezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only

Bezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only Edited: Yeh-Liag Hsu (998--; recommeded: Yeh-Liag Hsu (--9; last updated: Yeh-Liag Hsu (9--7. Note: This is the course material for ME55 Geometric modelig ad computer graphics, Yua Ze Uiversity. art of

More information

Counting Regions in the Plane and More 1

Counting Regions in the Plane and More 1 Coutig Regios i the Plae ad More 1 by Zvezdelia Stakova Berkeley Math Circle Itermediate I Group September 016 1. Overarchig Problem Problem 1 Regios i a Circle. The vertices of a polygos are arraged o

More information

Prime Cordial Labeling on Graphs

Prime Cordial Labeling on Graphs World Academy of Sciece, Egieerig ad Techology Iteratioal Joural of Mathematical ad Computatioal Scieces Vol:7, No:5, 013 Prime Cordial Labelig o Graphs S. Babitha ad J. Baskar Babujee, Iteratioal Sciece

More information

Graphs ORD SFO LAX DFW

Graphs ORD SFO LAX DFW Graphs SFO 337 1843 802 ORD LAX 1233 DFW Graphs A graph is a pair (V, E), where V is a set of odes, called vertices E is a collectio of pairs of vertices, called edges Vertices ad edges are positios ad

More information

A New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method

A New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method A ew Morphological 3D Shape Decompositio: Grayscale Iterframe Iterpolatio Method D.. Vizireau Politehica Uiversity Bucharest, Romaia ae@comm.pub.ro R. M. Udrea Politehica Uiversity Bucharest, Romaia mihea@comm.pub.ro

More information

Xiaozhou (Steve) Li, Atri Rudra, Ram Swaminathan. HP Laboratories HPL Keyword(s): graph coloring; hardness of approximation

Xiaozhou (Steve) Li, Atri Rudra, Ram Swaminathan. HP Laboratories HPL Keyword(s): graph coloring; hardness of approximation Flexible Colorig Xiaozhou (Steve) Li, Atri Rudra, Ram Swamiatha HP Laboratories HPL-2010-177 Keyword(s): graph colorig; hardess of approximatio Abstract: Motivated b y reliability cosideratios i data deduplicatio

More information

Lecture 18. Optimization in n dimensions

Lecture 18. Optimization in n dimensions Lecture 8 Optimizatio i dimesios Itroductio We ow cosider the problem of miimizig a sigle scalar fuctio of variables, f x, where x=[ x, x,, x ]T. The D case ca be visualized as fidig the lowest poit of

More information

Data Structures and Algorithms. Analysis of Algorithms

Data Structures and Algorithms. Analysis of Algorithms Data Structures ad Algorithms Aalysis of Algorithms Outlie Ruig time Pseudo-code Big-oh otatio Big-theta otatio Big-omega otatio Asymptotic algorithm aalysis Aalysis of Algorithms Iput Algorithm Output

More information

Algorithms for Disk Covering Problems with the Most Points

Algorithms for Disk Covering Problems with the Most Points Algorithms for Disk Coverig Problems with the Most Poits Bi Xiao Departmet of Computig Hog Kog Polytechic Uiversity Hug Hom, Kowloo, Hog Kog csbxiao@comp.polyu.edu.hk Qigfeg Zhuge, Yi He, Zili Shao, Edwi

More information

Sorting in Linear Time. Data Structures and Algorithms Andrei Bulatov

Sorting in Linear Time. Data Structures and Algorithms Andrei Bulatov Sortig i Liear Time Data Structures ad Algorithms Adrei Bulatov Algorithms Sortig i Liear Time 7-2 Compariso Sorts The oly test that all the algorithms we have cosidered so far is compariso The oly iformatio

More information

Big-O Analysis. Asymptotics

Big-O Analysis. Asymptotics Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses

More information

Hash Tables. Presentation for use with the textbook Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015.

Hash Tables. Presentation for use with the textbook Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015. Presetatio for use with the textbook Algorithm Desig ad Applicatios, by M. T. Goodrich ad R. Tamassia, Wiley, 2015 Hash Tables xkcd. http://xkcd.com/221/. Radom Number. Used with permissio uder Creative

More information

Solving Fuzzy Assignment Problem Using Fourier Elimination Method

Solving Fuzzy Assignment Problem Using Fourier Elimination Method Global Joural of Pure ad Applied Mathematics. ISSN 0973-768 Volume 3, Number 2 (207), pp. 453-462 Research Idia Publicatios http://www.ripublicatio.com Solvig Fuzzy Assigmet Problem Usig Fourier Elimiatio

More information

Numerical Methods Lecture 6 - Curve Fitting Techniques

Numerical Methods Lecture 6 - Curve Fitting Techniques Numerical Methods Lecture 6 - Curve Fittig Techiques Topics motivatio iterpolatio liear regressio higher order polyomial form expoetial form Curve fittig - motivatio For root fidig, we used a give fuctio

More information

Lecture 28: Data Link Layer

Lecture 28: Data Link Layer Automatic Repeat Request (ARQ) 2. Go ack N ARQ Although the Stop ad Wait ARQ is very simple, you ca easily show that it has very the low efficiecy. The low efficiecy comes from the fact that the trasmittig

More information

CSE 2320 Notes 8: Sorting. (Last updated 10/3/18 7:16 PM) Idea: Take an unsorted (sub)array and partition into two subarrays such that.

CSE 2320 Notes 8: Sorting. (Last updated 10/3/18 7:16 PM) Idea: Take an unsorted (sub)array and partition into two subarrays such that. CSE Notes 8: Sortig (Last updated //8 7:6 PM) CLRS 7.-7., 9., 8.-8. 8.A. QUICKSORT Cocepts Idea: Take a usorted (sub)array ad partitio ito two subarrays such that p q r x y z x y y z Pivot Customarily,

More information

The size Ramsey number of a directed path

The size Ramsey number of a directed path The size Ramsey umber of a directed path Ido Be-Eliezer Michael Krivelevich Bey Sudakov May 25, 2010 Abstract Give a graph H, the size Ramsey umber r e (H, q) is the miimal umber m for which there is a

More information

Chapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.

Chapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved. Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3

More information

Homework 1 Solutions MA 522 Fall 2017

Homework 1 Solutions MA 522 Fall 2017 Homework 1 Solutios MA 5 Fall 017 1. Cosider the searchig problem: Iput A sequece of umbers A = [a 1,..., a ] ad a value v. Output A idex i such that v = A[i] or the special value NIL if v does ot appear

More information

Mathematical Stat I: solutions of homework 1

Mathematical Stat I: solutions of homework 1 Mathematical Stat I: solutios of homework Name: Studet Id N:. Suppose we tur over cards simultaeously from two well shuffled decks of ordiary playig cards. We say we obtai a exact match o a particular

More information