Global
• 6 principal chapters on 45 hours for courses & exercises.
• 10 Labs (10%), 1 Assignment (10%)
• 2 evaluations: mid-exam (MCQ - 60 minutes - 40%) + final
exam (MCQ + writing - 120 minutes - 40%)
Aims
The content of this subject is mainly a great part of logic, set
theory and graph theory.
This is the mathematical base for many topics of Computational
Science
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Introduction
Huynh Tuong Nguyen,
Tran Huong Lan
Contents
Course description
Course outline
Document
Some applications
0.1
Chapter 0
Introduction
Discrete Structures for Computing on September 11, 2014
Huynh Tuong Nguyen, Tran Huong Lan
Faculty of Computer Science and Engineering
University of Technology - VNUHCM
Introduction
Huynh Tuong Nguyen,
Tran Huong Lan
Contents
Course description
Course outline
Document
Some applications
0.2
Contents
1 Course description
Course outline
Document
2 Some applications
Introduction
Huynh Tuong Nguyen,
Tran Huong Lan
Contents
Course description
Course outline
Document
Some applications
0.3
Context
Global
• 6 principal chapters on 45 hours for courses & exercises.
• 10 Labs (10%), 1 Assignment (10%)
• 2 evaluations: mid-exam (MCQ - 60 minutes - 40%) + final
exam (MCQ + writing - 120 minutes - 40%)
Aims
The content of this subject is mainly a great part of logic, set
theory and graph theory.
This is the mathematical base for many topics of Computational
Science
Introduction
Huynh Tuong Nguyen,
Tran Huong Lan
Contents
Course description
Course outline
Document
Some applications
0.4
Subjects in general discrete mathematics course
+ Logic
+ Set theory
+ Number theory
+ Combinatorics: enumerative combinatorics, graph theory
+ Algorithmics
+ Information theory
+ Complexity theory
+ Probability theory
+ Proof
+ Counting and Relations
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Tran Huong Lan
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0.5
Topics relational to the course
1 Theoretical computer science
2 Information theory
3 Logic
4 Set theory
5 Combinatorics
6 Graph theory
7 Probability
8 Number theory
9 Algebra
10 Calculus of finite differences, discrete calculus or discrete analysis
11 Geometry
12 Topology
13 Operations research: scheduling
14 Game theory, decision theory, utility theory, social choice theory
15 Discretization
16 Discrete analogues of continuous mathematics
17 . . .
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Tran Huong Lan
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0.6
Context
Course outline
• Proof methods
• modular arithmetic over integers.
• induction, contradiction.
• Set theory
• relations, functions, cardinalities, relation, equivalence equation, partial order
• combinatorics: counting, principles of sum, multiplication, division, inclusion
and exclusion.
• Graph theory
• directed, undirected, isomorphism
• weighted graphs, algorithm for finding shortest paths
• trees: features, binary trees, minimum spanning trees in connected and
weighted graphs
• flows network
• Probabilistics Modelling
• introductory random variables.
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Tran Huong Lan
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0.7
Document
Book
• Discrete mathematics and applications - Kenneth H. Rosen.
(Vietnamese translation - NXB KHKT 1997)
• Discrete mathematics - Richard Johnsonbaugh, Willey, 1997
• Discrete mathematics with algorithms - Micheal O. Albertson & Joan P.
Hutchinson, Willey, 1998
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Tran Huong Lan
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0.8
Application
• it concerns a wide range of disciplines in various areas: science, technology,
business and commerce.
• applied mathematicians are engaged in the creation, study and application of
advanced mathematical methods relevant to specific problems.
• applied mathematics has assumed a much broader meaning and embraces such
diverse fields as communication theory, optimization, game theory and numerical
analysis.
• today there is a remarkable variety of applications of mathematics in industry and
government, such as materials processing, design, medical diagnosis, development
of financial products, network management, weather prediction, etc.
Engineers use technology, mathematics and
scientific knowledge to solve practical
problems. (wikipedia.org)
Science
Technology
Engineering
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Computing of algorithm complexity
Know results
Size Approximating of computational time
n O(logn) O(n) O(n logn) O(n2) O(2n) O(n!)
10 3.10−9s 10−8s 3.10−8s 10−7s 10−6s 3.10−3s
102 7.10−9s 10−7s 7.10−7s 10−5s 4.1013y *
103 10−8s 10−6s 10−5s 10−3s * *
104 1, 3.10−8s 10−5s 10−4s 10−1s * *
105 1, 7.10−8s 10−4s 2.10−3s 10s * *
106 2.10−8s 10−3s 2.10−2s 17m * *
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Mathematical model
Solver
• Simplex, GLPK
• CPLEX, MPL
• Excel, Mathlab, etc.
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0.11
Mathematical model
Exercise
A bookseller A buys books from two publishers B, and C.
Publisher B offers a package of 5 mysteries and 5 romance novels
for $50, and publisher C offers a package of 5 mysteries and 10
romance novels for $150. The bookseller A wants to buy at least
2,500 mysteries and 3,500 romance novels, and he has promised C
(who has influence on the Senate Textbook Committee) that at
least 25% of the total number of books he purchases will come
from publisher C.
Question. How many packages should A order from each
publisher in order to minimize his cost and satisfy C ? What will
the novels cost him?
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Mathematical model
Solution
Let x be the number of packages from Publisher B, and let y be
the number of packages from C.
Problem: Minimize C = 50x+ 150y subject to
• 5x+ 5y ≥ 2.500
• 5x+ 10y ≥ 3.500
• x− 4.5y ≤ 0
• x ≥ 0, y ≥ 0
Answer: Buy 484 packages from Publisher B and 108 from C for a
total cost of $40.400.
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Graph
• Shortest path problem
• Min cut and maximum flow
• Vehicle Routing Problem
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0.14
Scheduling
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0.15
Scheduling
Exercise
Problem 1||Tmax.
Given 8 jobs with processing times and due dates as follows:
Job J1 J2 J3 J4 J5 J6 J7 J8
pi 1 2 2 3 3 4 4 3
di 25 16 19 7 18 22 27 8
Let Ci be completion time of job Ji and let Ti = max(0, Ci − di) its
tardiness.
Question. How to minimize Tmax = maxi Ti ? What is the minimum value of
Tmax ?
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Timetabling
Example
In the bipartite graph below, the vertices P1, . . . , P6 represent workers and
edges J1, . . . , J6 of jobs. An edge connects a worker with a job if the worker
has the necessary qualifications to occupy this job. Here, all the edges have an
unit weight 1, mean that Pi has the skill(competence) to operate Jj if there is
an edge between Pi and Jj .
P1 P2 P3 P4 P5 P6
J1 J2 J3 J4 J5 J6
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Game and simulation
Sally Salon Game
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0.18
Probabilistics Modelling
Calculating of Pi
Using a Monte-Carlo method to determine an approximate value
of pi :
randomly draw a great number of points in a square of side 2, and
determine the ratio C/N where N is the total number of points,
and C the number of points whose distance to the center of the
square is ≤ 1).