Discrete Optimization Lecture 4 – Part 1 M. Pawan Kumar Slides available online

Slides:



Advertisements
Similar presentations
Great Theoretical Ideas in Computer Science
Advertisements

Connectivity - Menger’s Theorem Graphs & Algorithms Lecture 3.
22C:19 Discrete Math Graphs Fall 2010 Sukumar Ghosh.
Graph-02.
13 May 2009Instructor: Tasneem Darwish1 University of Palestine Faculty of Applied Engineering and Urban Planning Software Engineering Department Introduction.
Great Theoretical Ideas in Computer Science for Some.
1 Slides based on those of Kenneth H. Rosen Slides by Sylvia Sorkin, Community College of Baltimore County - Essex Campus Graphs.
1 NP-completeness Lecture 2: Jan P The class of problems that can be solved in polynomial time. e.g. gcd, shortest path, prime, etc. There are many.
Great Theoretical Ideas in Computer Science.
1 Discrete Structures & Algorithms Graphs and Trees: II EECE 320.
Greedy Algorithms for Matroids Andreas Klappenecker.
Discrete Structures Chapter 7B Graphs Nurul Amelina Nasharuddin Multimedia Department.
Great Theoretical Ideas in Computer Science.
A general approximation technique for constrained forest problems Michael X. Goemans & David P. Williamson Presented by: Yonatan Elhanani & Yuval Cohen.
Approximation Algorithms
Marcelino Ibañez, C. M. and Guadalupe Rodríguez A note on some inequalities for the Tutte polynomial of a matroid.
Polyhedral Optimization Lecture 3 – Part 3 M. Pawan Kumar Slides available online
1 Set Theory. Notation S={a, b, c} refers to the set whose elements are a, b and c. a  S means “a is an element of set S”. d  S means “d is not an element.
Discrete Mathematics Lecture 9 Alexander Bukharovich New York University.
Minimum Spanning Trees. Subgraph A graph G is a subgraph of graph H if –The vertices of G are a subset of the vertices of H, and –The edges of G are a.
Introduction to Graph Theory
Polyhedral Optimization Lecture 3 – Part 2
GRAPH Learning Outcomes Students should be able to:
Polyhedral Optimization Lecture 1 – Part 1 M. Pawan Kumar Slides available online
Polyhedral Optimization Lecture 4 – Part 3 M. Pawan Kumar Slides available online
Polyhedral Optimization Lecture 5 – Part 1 M. Pawan Kumar Slides available online
Graphs – ADTs and Implementations ORD DFW SFO LAX
Linear Programming System of Linear Inequalities  The solution set of LP is described by Ax  b. Gauss showed how to solve a system of linear.
Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Sets.
1 ELEC692 Fall 2004 Lecture 1b ELEC692 Lecture 1a Introduction to graph theory and algorithm.
Based on slides by Y. Peng University of Maryland
Greedy Algorithms and Matroids Andreas Klappenecker.
Spring 2007Graphs1 ORD DFW SFO LAX
Chapter 2 Greedy Strategy I. Independent System Ding-Zhu Du.
Indian Institute of Technology Kharagpur PALLAB DASGUPTA Graph Theory: Introduction Pallab Dasgupta, Professor, Dept. of Computer Sc. and Engineering,
Polyhedral Optimization Lecture 4 – Part 2 M. Pawan Kumar Slides available online
Week 11 - Monday.  What did we talk about last time?  Binomial theorem and Pascal's triangle  Conditional probability  Bayes’ theorem.
Polyhedral Optimization Lecture 5 – Part 2 M. Pawan Kumar Slides available online
Introduction to Graph Theory
Graph Theory and Applications
 Quotient graph  Definition 13: Suppose G(V,E) is a graph and R is a equivalence relation on the set V. We construct the quotient graph G R in the follow.
Discrete Optimization Lecture 4 M. Pawan Kumar
Optimization - Lecture 5, Part 1 M. Pawan Kumar Slides available online
Submodularity Reading Group Matroids, Submodular Functions M. Pawan Kumar
Polyhedral Optimization Lecture 5 – Part 3 M. Pawan Kumar Slides available online
What is a matroid? A matroid M is a finite set E, with a set I of subsets of E satisfying: 1.The empty set is in I 2.If X is in I, then every subset of.
Week 11 - Wednesday.  What did we talk about last time?  Graphs  Paths and circuits.
1 GRAPH Learning Outcomes Students should be able to: Explain basic terminology of a graph Identify Euler and Hamiltonian cycle Represent graphs using.
Submodularity Reading Group Matroid Polytopes, Polymatroid M. Pawan Kumar
Submodularity Reading Group Matroids, Submodular Functions M. Pawan Kumar
Dilworth’s theorem and extremal set theory 張雁婷 國立交通大學應用數學系.
Polyhedral Optimization Lecture 2 – Part 2 M. Pawan Kumar Slides available online
Relations Binary relations represent relationships between the elements of two sets. A binary relation R from set A to set B is defined by: R  A 
Special Graphs By: Sandeep Tuli Astt. Prof. CSE.
Submodularity Reading Group More Examples of Matroids
Graph Theory and Algorithm 01
Advanced Algorithms Analysis and Design
Biconnectivity SEA PVD ORD FCO SNA MIA 11/16/2018 2:31 AM
Autumn 2016 Lecture 11 Minimum Spanning Trees (Part II)
Lecture 15: Graph Theory II
Autumn 2015 Lecture 11 Minimum Spanning Trees (Part II)
Chapter 9: Graphs Basic Concepts
CS 583 Analysis of Algorithms
Richard Anderson Lecture 10 Minimum Spanning Trees
Biconnectivity SEA PVD ORD FCO SNA MIA 5/6/2019 5:08 PM Biconnectivity
Winter 2019 Lecture 11 Minimum Spanning Trees (Part II)
Biconnectivity SEA PVD ORD FCO SNA MIA 5/23/ :21 PM
Applied Discrete Mathematics Week 13: Graphs
Chapter 9: Graphs Basic Concepts
Autumn 2019 Lecture 11 Minimum Spanning Trees (Part II)
Presentation transcript:

Discrete Optimization Lecture 4 – Part 1 M. Pawan Kumar Slides available online

€1000 €400 €700 Steal at most 2 items Greedy Algorithm €1000

€400 €700 Steal at most 1 item Greedy Algorithm €1000 €1700

€400 Steal at most 0 items Greedy Algorithm €1700 Success

€1000 €400 €700 2 kg 1 kg 1.5 kg Steal at most 2.5 kg Greedy Algorithm (Most Expensive) € kg

€400 €700 1 kg 1.5 kg Steal at most 0.5 kg Greedy Algorithm (Most Expensive) € kg Failure

€1000 €400 €700 2 kg 1 kg 1.5 kg Steal at most 2.5 kg Greedy Algorithm (Best Ratio) € kg

€400 €700 1 kg 1.5 kg Steal at most 0.5 kg Greedy Algorithm (Best Ratio) € kg Failure Why?

Matroids Examples of Matroids Dual Matroid Outline

Subset System Set S Non-empty collection of subsets I Property: If X  I and Y ⊆ X, then Y  I (S, I ) is a subset system

Hereditary Property Set S Non-empty collection of subsets I Property: If X  I and Y ⊆ X, then Y  I (S, I ) is a subset system

Example Set S = {1,2,…,m} I = Set of all X ⊆ S such that |X| ≤ k Is (S, I ) a subset system? Yes

Example Set S = {1,2,…,m}, w ≥ 0 I = Set of all X ⊆ S such that Σ s  X w(s) ≤ W Is (S, I ) a subset system YesNot true if w can be negative

Matroid Subset system (S, I ) Property: If X, Y  I and |X| < |Y| then there exists a s  Y\X M = (S, I ) is a matroid such that X ∪ {s}  I

Augmentation/Exchange Property Subset system (S, I ) Property: If X, Y  I and |X| < |Y| then there exists a s  Y\X M = (S, I ) is a matroid such that X ∪ {s}  I

Example Set S = {1,2,…,m} I = Set of all X ⊆ S such that |X| ≤ k Is M = (S, I ) a matroid?Yes Uniform matroid

Example Set S = {1,2,…,m}, w ≥ 0 I = Set of all X ⊆ S such that Σ s  X w(s) ≤ W Is M = (S, I ) a matroid?No Coincidence?No

Matroids (S, I ) is a matroid (S, I ) admits an optimal greedy algorithm

Matroids (S, I ) is a matroid (S, I ) admits an optimal greedy algorithm Why? We will find out by the end of the lecture

Matroids –Connection to Linear Algebra –Connection to Graph Theory Examples of Matroids Dual Matroid Outline

Matrix ASubset of columns {a 1,a 2,…,a k } Linearly independent (LI)? There exists no α ≠ 0 such that Σ i α i a i = 0 ✗

Matrix ASubset of columns {a 1,a 2,…,a k } Linearly independent (LI)? There exists no α ≠ 0 such that Σ i α i a i = 0 ✓

Matrix ASubset of columns {a 1,a 2,…,a k } Linearly independent (LI)? There exists no α ≠ 0 such that Σ i α i a i = 0 ✓

Matrix ASubset of columns {a 1,a 2,…,a k } Linearly independent (LI)? There exists no α ≠ 0 such that Σ i α i a i = 0 ✓

Matrix ASubset of columns {a 1,a 2,…,a k } Subset of LI columns are LI Define a subset system

Subset System Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent Is M = (S, I ) a matroid?

Answer Yes Matroids connected to Linear Algebra Inspires some naming conventions Linear Matroid

Independent Set Matroid M = (S, I ) X ⊆ S is independent if X  I X ⊆ S is dependent if X ∉ I

Independent Sets of Linear Matroid X ⊆ S is independent if column vectors A(X) are linearly independent Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X

Independent Sets of Uniform Matroid X ⊆ S is independent if |X| ≤ k S = {1,2,…,m} X ⊆ S

Base of a Subset Matroid M = (S, I ) X is a base of U ⊆ S if it satisfies three properties (i) X ⊆ U(ii) X ∈ I (iii) There exists no U’ ∈ I, such that X ⊂ U’ ⊆ U subset of Uindependent Inclusionwise maximal

Base of a Subset (Linear Matroid) U Is X a base of U? ✗

Base of a Subset (Linear Matroid) U ✗ Is X a base of U?

Base of a Subset (Linear Matroid) U ✓ Is X a base of U?

Base of a Subset (Linear Matroid) U ✗ Is X a base of U?

Base of a Subset (Linear Matroid) U ✓ Is X a base of U?

Base of a Subset (Linear Matroid) U Is X a base of U? ✓

Base of a Subset (Linear Matroid) U Base of U?

Base of a Subset (Linear Matroid) X ⊆ S is base of U if A(X) is a base of A(U) Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Base of a Subset (Uniform Matroid) X ⊆ S is base of U if X ⊆ U and |X| = min{|U|,k} S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

An Interesting Property M = (S, I ) is a subset system M is a matroid For all U ⊆ S, all bases of U have same size Proof?

An Interesting Property M = (S, I ) is a subset system M is a matroid For all U ⊆ S, all bases of U have same size Proof?

An Interesting Property M = (S, I ) is a subset system M is a matroid For all U ⊆ S, all bases of U have same size An alternate definition for matroids

Rank of a Subset Matroid M = (S, I ) U ⊆ S r M (U) = Size of a base of U

Rank of a Subset (Linear Matroid) U r M (U)? 2

Rank of a Subset (Linear Matroid) U r M (U)? 1

Rank of a Subset (Linear Matroid) r M (U) is equal to rank of the matrix with columns A(U) Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Rank of a Subset (Uniform Matroid) r M (U) is equal to min{|U|,k} S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

Base of a Matroid Matroid M = (S, I ) X is a base S

Base of a Linear Matroid Is X a base? ✗

Base of a Linear Matroid Is X a base? ✓

Base of a Linear Matroid X ⊆ S is base of the matroid if A(X) is a base of A Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Base of a Uniform Matroid X ⊆ S is a base of the matroid if |X| = min{|S|,k}Assume k ≤ |S| S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

Base of a Uniform Matroid X ⊆ S is a base of the matroid if |X| = k S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k Assume k ≤ |S|

Rank of a Matroid Matroid M = (S, I ) r M = Rank of S

Rank of a Linear Matroid rM?rM? 3

r M is equal to rank of the matrix A Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Rank of a Uniform Matroid r M is equal to k S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

Spanning Subset Matroid M = (S, I ) U ⊆ S U is spanning if it contains a base of the matroid

True or False A base is an inclusionwise minimal spanning subset TRUE

Spanning Subsets of Linear Matroid Is X a spanning subset? ✗

Spanning Subsets of Linear Matroid Is X a spanning subset? ✓

Spanning Subsets of Linear Matroid Is X a spanning subset? ✓

Spanning Subsets of Linear Matroid U ⊆ S is spanning subset of the matroid if A(U) spans A Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Spanning Subsets of Uniform Matroid U ⊆ S is a spanning subset of the matroid if |X| ≥ k S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

Recap What is a subset system? Bases of a subset of a matroid? Rank r M (U) of a subset U? What is a matroid? Spanning subset?

Matroids –Connection to Linear Algebra –Connection to Graph Theory Examples of Matroids Dual Matroid Outline

Undirected Graph v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Parallel edgesLoop

Walk G = (V, E) Sequence P = (v 0,e 1,v 1,…,e k,v k ), e i = (v i-1,v i ) v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 v 0, (v 0,v 4 ), v 4, (v 4,v 2 ), v 2, (v 2,v 5 ), v 5, (v 5,v 4 ), v 4 V = {v 1,…,v n } E = {e 1,…,e m }

Path G = (V, E) Sequence P = (v 0,e 1,v 1,…,e k,v k ), e i = (v i-1,v i ) v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Vertices v 0,v 1,…,v k are distinct V = {v 1,…,v n } E = {e 1,…,e m }

Connected Graph v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } There exists a walk from one vertex to another Connected?

k-Vertex-Connected Graph v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Remove any i < k vertices. Graph is connected. 2-Vertex-Connected?3-Vertex-Connected?

Circuit G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Circuit = (v 0,e 1,v 1,…,e k,v k ), e i = (v i-1,v i ) v 0 = v k Vertices v 0,v 1,…,v k-1 are distinct 1-circuit? 2-circuit?

Forest v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Subset of edges that contain no circuit

Forest v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Subset of edges that contain no circuit Forest?

Forest v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Subset of edges that contain no circuit Forest?

Forest v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Subset of edges that contain no circuit Forest?

Forest v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } Define a subset system on forests Subset of a forest is a forest

Subset System v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) V = {v 1,…,v n } E = {e 1,…,e m } S = ES = E X ⊆ S X ∈ I if X is a forest Is M = (S, I ) a matroid?

Answer Yes Matroids connected to Graph Theory Inspires some naming conventions Cycle Matroid Graphic matroids (isomorphic to cycle matroid)

Circuit Matroid M = (S, I ) X is a circuit if it satisfies three properties (i) X ⊆ S(ii) X ∉ I (iii) There exists no Y ∉ I, such that Y ⊂ X subset of Sdependent Inclusionwise minimal

Circuit of a Graphic Matroid v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Is this a circuit?

Circuit of a Graphic Matroid v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Is this a circuit?

Circuit of a Graphic Matroid v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Is this a circuit?

Circuit of a Graphic Matroid G = (V, E), S = E X ⊆ S X ∈ I if X is a forest X ⊆ S is a circuit if X is a circuit of G

Circuit of a Uniform Matroid X ⊆ S is a circuit if |X| = k+1 S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

Circuit of a Linear Matroid X ⊆ S is a circuit if A(X) = {a base of A } ∪ {any other column of A} Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Circuit of a Linear Matroid X ⊆ S is a circuit if A(X) = two linearly dependent columns Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Loop Matroid M = (S, I ) Element s ∈ S {s} is a circuit

Loop of a Graphic Matroid v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Any loops in the matroid?

Loop of a Graphic Matroid G = (V, E), S = E X ⊆ S X ∈ I if X is a forest s ∈ S is a loop if {s} is a loop of G

Loop of a Uniform Matroid S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k s ∈ S is a loop if k = 0

Loop of a Linear Matroid Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent s ∈ S is a loop if A(s) = 0

Parallel Elements Matroid M = (S, I ) Elements s,t ∈ S {s,t} is a circuit

v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 Any parallel elements? Parallel Elements of a Graphic Matroid

G = (V, E), S = E X ⊆ S X ∈ I if X is a forest s,t ∈ S are parallel if {s,t} are parallel edges of G

Parallel Elements of a Uniform Matroid S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k s,t ∈ S are parallel elements if k = 1

Parallel Elements of a Linear Matroid Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent s,t ∈ S are parallel elements if A(s) and A(t) are linearly dependent

Recap What is a subset system? Bases of a subset of a matroid? Rank r M (U) of a subset U? What is a matroid? Spanning subset?

Recap Circuit? Parallel elements? Loop?

Matroids Examples of Matroids Dual Matroid Outline

Uniform Matroid S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k

Linear Matroid Matrix A of size n x m, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent

Graphic Matroid G = (V, E), S = E X ⊆ S X ∈ I if X is a forest

Matroids Examples of Matroids –Partition Matroid –Transversal Matroid –Matching Matroid Dual Matroid Outline

Partition Set S Non-empty subsets {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} Mutually exclusive S i ∩ S j = ϕ, for all i ≠ j Collectively exhaustive ∪ i S i = S {{1, 2, 3}, {4, 5, 6}, {7, 8}}? Partition {S i }

Partition Set S Non-empty subsets {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} Mutually exclusive S i ∩ S j = ϕ, for all i ≠ j Collectively exhaustive ∪ i S i = S {{1, 2, 3}, {4, 5, 6, 7}, {7, 8, 9}}? Partition {S i }

Partition Set S Non-empty subsets {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} Mutually exclusive S i ∩ S j = ϕ, for all i ≠ j Collectively exhaustive ∪ i S i = S {{1, 2, 3}, {4, 5, 6, 7}, {8, 9}}? Partition {S i }

Partition Set S{1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {8, 9}} Partition {S i }

Limited Subset of Partition Set S{1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {8, 9}} Partition {S i } Limits {l i } Limited Subset (LS) X ⊆ S |X ∩ S i | ≤ l i, for all i {1, 2, 4, 5, 6, 8}?

Limited Subset of Partition Set S{1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {8, 9}} Partition {S i } Limits {l i } Limited Subset (LS) X ⊆ S |X ∩ S i | ≤ l i, for all i {1, 2, 4, 5, 8}?

Limited Subset of Partition Set S{1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {8, 9}} Partition {S i } Limits {l i } Limited Subset (LS) X ⊆ S {1, 2, 4, 5}? |X ∩ S i | ≤ l i, for all i

Limited Subset of Partition Set S{1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {8, 9}} Partition {S i } Limits {l i } Limited Subset (LS) X ⊆ S Subset of an LS is an LSSubset system |X ∩ S i | ≤ l i, for all i

Subset System Set S {S i, i = 1, 2, …, n} is a partition {l 1,l 2,…,l n } are non-negative integers X ⊆ S ∈ I if X is a limited subset of partition

Subset System {l 1,l 2,…,l n } are non-negative integers X ⊆ S ∈ I if |X ∩ S i | ≤ l i for all i ∈ {1,2,…,n} (S, I ) is a matroid? Partition Matroid Set S {S i, i = 1, 2, …, n} is a partition

Matroids Examples of Matroids –Partition Matroid –Transversal Matroid –Matching Matroid Dual Matroid Outline

Partial Transversal Set S S 1, S 2, …, S n ⊆ S (not necessarily disjoint) X ⊆ S is a partial transversal (PT) of {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} X = {x 1,…,x k }, each x j chosen from a distinct S i {{1, 2, 3}, {4, 5, 6, 7}, {7, 8, 9}} {S i } {1, 4, 7, 8}?

Partial Transversal Set S S 1, S 2, …, S n ⊆ S (not necessarily disjoint) X ⊆ S is a partial transversal (PT) of {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {7, 8, 9}} {S i } {1, 7, 8}? X = {x 1,…,x k }, each x j chosen from a distinct S i

Partial Transversal Set S S 1, S 2, …, S n ⊆ S (not necessarily disjoint) X ⊆ S is a partial transversal (PT) of {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {7, 8, 9}} {S i } {1, 7}? X = {x 1,…,x k }, each x j chosen from a distinct S i

Partial Transversal Set S S 1, S 2, …, S n ⊆ S (not necessarily disjoint) X ⊆ S is a partial transversal (PT) of {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {7, 8, 9}} {S i } {7}? X = {x 1,…,x k }, each x j chosen from a distinct S i

Partial Transversal Set S S 1, S 2, …, S n ⊆ S (not necessarily disjoint) X ⊆ S is a partial transversal (PT) of {S i } {1, 2, 3, 4, 5, 6, 7, 8, 9} {{1, 2, 3}, {4, 5, 6, 7}, {7, 8, 9}} {S i } Subset of a PT is a PTSubset system X = {x 1,…,x k }, each x j chosen from a distinct S i

Subset System Set S S 1, S 2, …, S n ⊆ S (not necessarily disjoint) X ⊆ S ∈ I if X is a partial transversal of {S i } (S, I ) is a matroid?Transversal Matroid

Matroids Examples of Matroids –Partition Matroid –Transversal Matroid –Matching Matroid Dual Matroid Outline

Matching v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) Matching is a set of disjoint edges. No two edges in a matching share an endpoint.

Matching v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) Matching is a set of disjoint edges. No two edges in a matching share an endpoint. ✓

Matching v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) Matching is a set of disjoint edges. No two edges in a matching share an endpoint. ✗

Matching Matroid v1v1 v1v1 v0v0 v0v0 v2v2 v2v2 v6v6 v6v6 v4v4 v4v4 v5v5 v5v5 v3v3 v3v3 G = (V, E) X ⊆ S ∈ I if a matching covers X S = V (S, I ) is a matroid?Matching Matroid

Matroids Examples of Matroids Dual Matroid Outline

Dual Matroid M = (S, I )M* = (S, I *) X ∈ I * if two conditions are satisfied (i) X ⊆ S (ii) S\X is a spanning set of M Bases of M, M* are complements of each other If M* is also a matroid then

Dual of Graphic Matroid G = (V, E), S = E X ⊆ S X ∈ I if X is a forest Y ∈ I * if E\Y contains a maximal forest of G

Dual of Graphic Matroid G = (V, E), S = E X ⊆ S X ∈ I if X is a forest Y ∈ I * if, after removing Y, number of connected components don’t change Cographic Matroid

Dual of Uniform Matroid S = {1,2,…,m} X ⊆ S I = Set of all X ⊆ S such that |X| ≤ k Y ∈ I * if |Y| ≤ m-k

Dual of Linear Matroid Matrix A of size m x n, S = {1,2,…,m} X ⊆ S, A(X) = set of columns of A indexed by X X  I if and only if A(X) are linearly independent Y ∈ I * if A(S\Y) spans A

Dual Matroid is a Subset System Proof?

Dual Matroid is a Matroid Proof?

Dual Matroid is a Matroid M = (S, I )M* = (S, I *) Let X ∈ I * and Y ∈ I *, such that |X| < |Y| There should exist s ∈ Y\X, X ∪ {s} ∈ I * S\Y contains a base of MWhy? S\X contains a base of M

Dual Matroid is a Matroid S\Y contains a base of MB S\X contains a base of M B\X ⊆ S\X B’ ⊆ Base B’ There exists s ∈ Y\X, s ∉ B’ Proof? By contradiction

Dual Matroid is a Matroid B\X ⊆ S\X B’ ⊆ Base B’ There exists s ∈ Y\X, s ∉ B’ |B| = |B ∩ X| + |B \ X| ≤ |X \ Y| + |B \ X|Why? Because B is disjoint from Y

Dual Matroid is a Matroid B\X ⊆ S\X B’ ⊆ Base B’ |B| = |B ∩ X| + |B \ X| ≤ |X \ Y| + |B \ X| < |Y \ X| + |B \ X|Why? Because |X| < |Y| There exists s ∈ Y\X, s ∉ B’

Dual Matroid is a Matroid B\X ⊆ S\X B’ ⊆ Base B’ |B| = |B ∩ X| + |B \ X| ≤ |X \ Y| + |B \ X| < |Y \ X| + |B \ X| Why? Because Y\X ⊆ B’ ≤ |B’| B\X ⊆ B’ B ∩ Y = ϕ There exists s ∈ Y\X, s ∉ B’

Dual Matroid is a Matroid B\X ⊆ S\X B’ ⊆ Base B’ |B| = |B ∩ X| + |B \ X| ≤ |X \ Y| + |B \ X| < |Y \ X| + |B \ X| Contradiction≤ |B’| There exists s ∈ Y\X, s ∉ B’

Dual Matroid is a Matroid B\X ⊆ S\X B’ ⊆ Base B’ There exists s ∈ Y\X, X ∪ {s} ∈ I * Hence proved. There exists s ∈ Y\X, s ∉ B’

Dual Matroid is a Matroid Circuits of M* are called cocircuits of M Loops of M* are called coloops of M Parallel elements in M* are coparallel in M

Dual of Dual Matroid is the Matroid Proof?

Ranking Functions of M and M* M = (S, I )M* = (S, I *) r M* (U) = |U| + r M (S\U) - r M (S) Proof?

Ranking Functions of M and M* M = (S, I )M* = (S, I *) r M* (U) = max{|U \ Y|, Y is a base of M} = |U| - min{|U ∩ Y|, Y is a base of M} = |U| + max{|Y\U|, Y is a base of M} - |Y| = |U| + r M (S \ U) - r M (S) = max{|U ∩ X|, X is a base of M*}

Connected Matroid Matroid M = (S, I ) For all non-empty U ⊂ S r M (U) + r M (S\U) > r M (S) M is connected if and only if M* is connected