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

Ders Genel Tanıtım Bilgileri

Course Code:

1411002008

Ders İsmi:

Heuristic Optimization

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 Elif TARAKÇI

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	As per the learning paradigm, after successfully completing this class, students will be able to: How and why heuristics and metaheuristics teckniques work. Under what circumstances metaheuristics should be used Advantages and disadvantages of heuristics and metaheuristics over other(deterministic..) methodologies.
Course Content:	Available and newly introduced heauristic methods to solve/optimize combinatirial problems. Objective, abilities and practical applications of heuristic methods in optimization theory.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Students will use the knowledge on simulating annealing, genetic algorithms, TABU search and other heuristic methodologies.
2) Student will be able to model,apply and analyse heuristic methods
3) Student will be able to apply neural networks and some other important heuristic methods.
2 - Skills
Cognitive - Practical
1) Student will be able to analyse the results that s/he gained by applying heauristic methods, and compare with deterministic (exact) solution methodologies.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction to exponential complexity and algorithmic combinatorial problems	Lecture Notes
2)	Branch and Bound Algorithm	Lecture Notes
3)	Dominancy, bound relaxation and integer programming	Lecture Notes
4)	Lagrangean Relaxation	Lecture Notes
5)	Lagrangean Relaxation	Lecture Notes
6)	Neighborhood searching: Local and global optimality	Lecture Notes
7)	Neighborhood searching: Fixing heuristics	Lecture Notes
8)	Mid-Term	Lecture Notes
9)	Genetic Algorithms: populations, generation and crossover	Lecture Notes
10)	Mutation, genetic modeling	Lecture Notes
11)	TABU Search: Short time memory, goal, strenghting, diversification	Lecture Notes
12)	Other methodologies: neual networks	Lecture Notes
13)	Hybrid techniques	Lecture Notes
14)	Deluge algorithm	Lecture Notes
15)	Final Exam	Lecture Notes

Sources

Course Notes / Textbooks:	Ders Notları
References:	El-G. Talbi, Metaheuristics: From Design to Implementation, John Wiley & Sons, New York, 2009. • D.E. Goldberg, Genetic Algorithms In Search, Optimization And Machine Learning, Addison-Wesley Professional, New York, 1989. (Other References) C.R. Reeves. Modern Heuristic Techniques for Combinatorial Problems, John Wiley & Sons, New York, 1993.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4
Program Outcomes
1) Adequate knowledge of mathematics (a), science (b) and industrial engineering (c) (1) and the ability to use this knowledge in complex engineering problems.
2) Ability to work effectively both individually and in interdisciplinary and multidisciplinary teams.
3) Awareness of the necessity of lifelong learning and the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
4) Knowledge of project management, risk management, innovation and change management, entrepreneurship and sustainable development
5) Awareness of the sectors and the ability to prepare a business plan.
6) Professional and ethical responsibility awareness and acting in accordance with ethical principles.
7) Information about the problems of the age in the field of engineering and the effects and legal consequences of engineering practices on health, environment and safety in universal and social dimensions.
8) Information about current engineering practices and standards used in engineering practices.
9) The ability to identify, formulate and solve complex engineering problems, and the ability to select and apply appropriate analysis and modeling methods for this purpose.
10) The ability to design a complex system, process, device or product using modern methods under realistic constraints and conditions and to meet specific requirements.
11) The ability to develop, select and use modern techniques and tools necessary for the solution of engineering problems, and the ability to use information technologies effectively.
12) Ability to design and conduct experiments, collect data, analyze data and interpret results for the study of engineering problems or research issues.
13) Ability to communicate effectively, write reports and make presentations in Turkish and English with oral, written and visual methods.
14) In-depth knowledge of appropriate analytical and experimental methods and computational methods for system integration such as simulation (a), production systems (b) operations research (c) and statistics (d).
15) Skills in designing (a) and improving (b), defining goals and criteria (c), analyzing (d) and developing solutions (e) systems that include people, materials, information, equipment and energy to creatively solve real-life problems

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	Adequate knowledge of mathematics (a), science (b) and industrial engineering (c) (1) and the ability to use this knowledge in complex engineering problems.
2)	Ability to work effectively both individually and in interdisciplinary and multidisciplinary teams.
3)	Awareness of the necessity of lifelong learning and the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
4)	Knowledge of project management, risk management, innovation and change management, entrepreneurship and sustainable development
5)	Awareness of the sectors and the ability to prepare a business plan.
6)	Professional and ethical responsibility awareness and acting in accordance with ethical principles.
7)	Information about the problems of the age in the field of engineering and the effects and legal consequences of engineering practices on health, environment and safety in universal and social dimensions.
8)	Information about current engineering practices and standards used in engineering practices.
9)	The ability to identify, formulate and solve complex engineering problems, and the ability to select and apply appropriate analysis and modeling methods for this purpose.
10)	The ability to design a complex system, process, device or product using modern methods under realistic constraints and conditions and to meet specific requirements.
11)	The ability to develop, select and use modern techniques and tools necessary for the solution of engineering problems, and the ability to use information technologies effectively.
12)	Ability to design and conduct experiments, collect data, analyze data and interpret results for the study of engineering problems or research issues.
13)	Ability to communicate effectively, write reports and make presentations in Turkish and English with oral, written and visual methods.
14)	In-depth knowledge of appropriate analytical and experimental methods and computational methods for system integration such as simulation (a), production systems (b) operations research (c) and statistics (d).
15)	Skills in designing (a) and improving (b), defining goals and criteria (c), analyzing (d) and developing solutions (e) systems that include people, materials, information, equipment and energy to creatively solve real-life problems

Öğrenme Etkinliği ve Öğretme Yöntemleri

Anlatım
Course

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

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	13	2	26
Study Hours Out of Class	13	2	26
Homework Assignments	2	11	22
Midterms	1	10	10
Final	1	15	15
Total Workload			99