SULEYMAN DEMIREL UNIVERSITY
FACULTY OF ENGINEERING
DEPARTMENT of INFORMATION SYSTEMS
APPROVED BY
The Dean of the Engineering Faculty
__________.
«_____» _________ 2015
Discipline: CSS301 MODELS AND METHODS IN CONTROL THEORY
Number of credits: 2 credits
Term: Spring 2015
Instructor’s full name: Mr. Bakhyt Bakiyev
Time and place
Room
Bakhyt Bakiyev K.
404
Office hours
by appointment
Contact information
Tel.:
87752838886
e-mail
bakhit.bakiev
@sdu.edu.kz
Pre-requisites
Linear algebra, geometry and discrete mathematics
Post-requisites
Operations research
Course goals and objectives
•
•
•
A primary objective is to give students general knowledge of basics of optimization course.
Understand the basic theory behind LP, algorithms to solve LPs, and the basics of (mixed)
integer programs.
Understand important and emerging applications of LP to economic problems (optimal
resource allocation), diet problem, transportation problems, assignment problems, and so on.
At the end of the course, the successful student will be able to cast various problems that may
arise in her research as optimization problems, understand the cases where the optimization
problem will be linear, choose appropriate solution methods and interpret results
appropriately. This is generally considered a useful ability in many research areas.
Literature
1. “Operations Research: An Introduction”, Hamdy A. Taha.
2. “Введение в исследование операций”, Хэмди А. Таха.
3. “Математические методы и модели в управлении”, Е. В. Шикин, А. Г. Чхартишвили.
1.
2.
3.
4.
5.
Supplementary
Linear Programming: Foundations and Extensions, Second Edition, Robert J. Vanderbei, 2001
Introduction to Linear Optimization, 1st edition, Dimitris Bertsimas, John N Tsitsiklis
Understanding and Using Linear Programming, 1st edition, Jiri Matousek, Bernd Gartner
Theory of Linear and Integer Programming, Alexander Schrijver, 1998
Linear Programming 1: Introduction, George B. Dantzig, Mukund N. Thapa, 1997
Curriculum Plan:
Classroom
Week
Topic
Lectures Practica
l classes
Chapters for reading
Minutes
Minutes
Introduction to Linear
Programming.
Linear Programming
Formulations.
How to Solve Linear
Problems by
Graphical method.
Linear Programming
Formulations.
How to Solve Linear
Problems by
Algebraic method.
The Simplex
Algorithm (basics).
Diet problem.
Big-M method to solve
simplex method.
50
50
Ch.1 and Ch.2
Operations research, Hamdy A. Taha, 8th
edition
50
50
Ch.2 and Ch.3
Operatios research, Hamdy A. Taha, 8th
edition
50
50
50
50
5.
Two phase method to
solve simplex method.
50
50
6.
More details on
Simplex: Handling
unbounded problems.
Initialization Phase
50
50
Ch.3
Operatios research, Hamdy A. Taha, 8th
edition
Ch.3
Operatios research, Hamdy A. Taha, 8th
edition
Ch.3
Operatios research, Hamdy A. Taha, 8th
edition
Ch.3
Operatios research, Hamdy A. Taha, 8th
edition
1.
2.
3.
4.
7-8.
Simplex.
Cycling and the Use of
Bland's rule.
Complexity of
Simplex.
Duality: dual variables 100
and dual linear
program.
Strong duality theorem.
Complementary
Slackness.
Understanding the dual
problem: shadow costs
100
Ch.4
Operatios research, Hamdy A. Taha, 8th
edition
Introduction to
50
Transportation
problem.
A. Balanced type:
1) Northwest Corner
cell method.
2) Least cost cell
method.
3) Vogal’s
Approximation
method.
Optimization Check for 100
Transport problem
solutions:
1) Stepping Stone
method.
2) MODI method for
transportation
problems.
Transportation
50
problem:
B. Unbalanced type.
50
Ch.5
Operatios research, Hamdy A. Taha, 8th
edition
100
Ch.5
Operatios research, Hamdy A. Taha, 8th
edition
50
Assignment problem:
A. Balanced type.
Hungarian algorithm.
B. Unbalanced type.
100
Ch.5
Operatios research, Hamdy A. Taha, 8th
edition
Ch.6
Operatios research, Hamdy A. Taha, 8th
edition
Midterm -1
9.
10-11.
12.
13-14.
Midterm-2
100
17-16
Final
Grading criteria
Types of tasks
Mid-term exams (midterm1 and midterm2)
Final exam
Total
Scores
60
40
100
This table provides criteria for assessing the knowledge and the delivery schedule of the tasks.
Each teacher defines the types of tasks and evaluation depending on the specifics of their students
Schedule of performance and delivery of works
№
Week
Total
Type of evaluation
1
2
3
4
5 6
7
8
9 10 11 12
13 14 15
1
Attendance and
participation
*
*
*
*
* *
*
*
*
*
*
*
*
*
2
6
7
Practical lessons
Mid-term exam
Final exam
Total
*
*
*
*
* *
*
*
*
*
*
*
*
*
*
16-17
*
0
*
*
Knowledge control forms:
Practical classes: 15 times in a semester
Midterm Examination: 2 times in a semester
Final Examination: 1 time in a semester, within period of examination session
Academic Policy
SDU standard academic policy is used.
0
60
40
100
-
-
Cheating, duplication, falsification of data, plagiarism, and crib are not permitted under any
circumstances!
Attendance is mandatory. Attention. Missing 20% attendance to lessons, student will be taken from
discipline with filling in F (Fail) grade.
Students must participate fully in every class. While attendance is crucial, merely being in class does
not constitute “participation”. Participation means reading the assigned materials, coming to class
prepared to ask questions and engage in discussion.
Students must arrive to class on time.
Make up Midterms in case of absence will not normally be allowed.
Mobile phones must always be switched off in class.
Students should always show tolerance, consideration and mutual support towards other students.
When evaluation of students during semester those described below should be necessarily taken into
account:
- Actively and productively participation to practical study
- Performance of task
- Performance of individual research project
- Submission all work on time (deadline)
Author Mr. Bakhyt Bakiyev
Considered in meeting at Departments of Information Systems,
transaction №
in «__» _______ ____ year.