DEPARTMENT OF SOFTWARE ENGINEERING (ENGLISH)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1413002001

Ders İsmi:

Genetic Algorithms

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Department Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi Adem ÖZYAVAŞ

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	Classical optimization used in solving multi-parameter problems In addition to the techniques of genetic algorithms developed, solution and to show its benefits in analysis. Problem solving with this benefit aimed at enhancing their capabilities.
Course Content:	Solution of NP problems with genetic algorithms, solution evaluations and analysis techniques. Computer applications of these algorithms

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
1) Students will be able to analyze finite automata, deterministic and non-deterministic automata, regular expressions, push automata, turing machines, formal languages and grammars.
3 - Competences
Communication and Social Competence
Learning Competence
1) 1- Understanding basic optimization concepts 2- Understanding genetic algorithm operators 3- Understanding hybrid genetic algorithms 4- Understanding the types of genetic algorithms 5- Understanding alternative algorithms
2) Students will be able to design for finite automata, deterministic and non-deterministic automata, regular expressions, push automata, turing machines, formal languages and grammars.
Field Specific Competence
1) Students will demonstrate an understanding of key concepts such as algorithm, computability, decidability, and complexity through problem solving.
2) Students will become familiar with Turing Machines and Problem Classes.
Competence to Work Independently and Take Responsibility
1) Students will develop their problem posing and solving skills.
2) Students will be able to prove the basic results of the Theory of Computation.

Ders Akış Planı

Week	Subject	Related Preparation
1)	Formation of preliminary concepts, mathematical tools, definitions, theorems and proofs, types of proofs	Relevant section of the textbook
2)	Deterministic finite automata (DFA)	Relevant section of the textbook
3)	Non-deterministic finite automata (NFA)	Course Lecture
4)	Equivalence of DFA and NFA and regular expressions	Lecture Notes
5)	Epsilon transition, pumping Lemma, pigeon principle and closure features	Lecture Notes
6)	Optimal DFA and overview	Lecture Notes
7)	Context-free languages, context-free grammars, parse tree, ambiguity, closure properties	Lecture Notes
8)	Midterm Exam 1	Lecture Notes
9)	In-year exam	Lecture Notes
10)	Stacked Vending Machines	Lecture Notes
11)	Overview of context-free grammars and the Church-Turing hypothesis	Lecture Notes
12)	Turing Machines, Recognition and Computation, Church-Turing Hypothesis	Lecture Notes
13)	Midterm 2
14)	Equivalence of DFA and NFA and regular expressions	Lecture Notes
15)	NP-completeness, decidability, reducibility and recognizability	Lecture Notes
16)	Final

Sources

Course Notes / Textbooks:	DERS KİTABI - COURSE BOOK
References:

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	1	3	4	5	6
Program Outcomes
1) Competent knowledge of mathematics, science and technology, and computer engineering; ability to apply this knowledge to engineering solutions.
2) Skills to design and conduct experiments, collect data, analyze and interpret results.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4) Ability to develop, select and use modern techniques and tools required for analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
5) Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics.
6) Ability to work effectively in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in Turkish, both orally and in writing; Knowledge of at least one foreign language; the ability to write and understand written reports effectively, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the necessity of lifelong learning; the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
9) Acting in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications.
10) Information about business life practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.
11) Knowledge about the universal and social effects of engineering applications on health, environment and safety and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Competent knowledge of mathematics, science and technology, and computer engineering; ability to apply this knowledge to engineering solutions.
2)	Skills to design and conduct experiments, collect data, analyze and interpret results.
3)	Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools required for analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
5)	Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics.
6)	Ability to work effectively in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7)	Ability to communicate effectively in Turkish, both orally and in writing; Knowledge of at least one foreign language; the ability to write and understand written reports effectively, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
9)	Acting in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications.
10)	Information about business life practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.
11)	Knowledge about the universal and social effects of engineering applications on health, environment and safety and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 30
Midterms	1	% 30
Semester Final Exam	1	% 40
total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	12	3	36
Study Hours Out of Class	11	3	33
Homework Assignments	2	10	20
Midterms	1	25	25
Final	1	35	35
Total Workload			149