Endüstri Mühendisliği

IE 357 | Ders Tanıtım Bilgileri

Dersin Adı

Special Topics in Optimization

Kodu	Yarıyıl	Teori (saat/hafta)	Uygulama/Lab (saat/hafta)	Yerel Kredi	AKTS
IE 357	FALL	3	0	3	6

Ön-Koşul(lar)	IE 252 To be successful (To have received at least DD grade)
Dersin Dili	English
Dersin Türü	ELECTIVE_COURSE
Dersin Düzeyi	Lisans
Dersin Veriliş Şekli	Face-To-Face
Dersin Öğretim Yöntem ve Teknikleri	Lecture / Presentation
Ulusal Meslek Sınıflandırma Kodu	-
Dersin Koordinatörü	Prof. Dr. Selin Özpeynirci
Öğretim Eleman(lar)ı	Prof. Dr. Selin Özpeynirci
Yardımcı(ları)	-

Dersin Amacı

This course aims to teach advanced solution techniques and algorithms for large-scale integer programming problems. It covers methods such as linear programming relaxations, Dantzig-Wolfe decomposition, branch-and-bound algorithm, Lagrangian relaxation, cutting plane methods, Benders decomposition, and dynamic programming. The course seeks to provide students with a comprehensive understanding of the theoretical foundations and practical applications of these techniques.

Öğrenme Çıktıları

Bu dersi başarıyla tamamlayabilen öğrenciler;

Ad	Açıklama	PC Alt	* Katkı Düzeyi
Ad	Açıklama	PC Alt	1	2	3	4	5
LO1	Students will be able to identify the limitations of classical optimization techniques.	1.5			X
LO2	Students will be able to explain the principles of linear programming relaxation.	4				X
LO3	Students will be able to apply methods such as Dantzig-Wolfe decomposition, branch-and-bound algorithm, and Lagrangian relaxation to large-scale integer programming problems, along with their justifications.	4				X
LO4	Students will be able to adapt Benders decomposition and dynamic programming techniques to solve various optimization problems encountered in practice.	4				X

Ders Tanımı

Classical Optimization Methods, Linear Programming Relaxation, Dantzig-Wolfe Decomposition, Branch-and-Bound Algorithm, Lagrangian Relaxation, Cutting Plane Method, Benders Decomposition

Dersin İlişkili Olduğu Sürdürülebilir Kalkınma Amaçları

Dersin Kategorisi	Temel Ders
	Uzmanlık/Alan Dersleri	X
	Destek Dersleri
	İletişim ve Yönetim Becerileri Dersleri
	Aktarılabilir Beceri Dersleri

HAFTALIK KONULAR VE İLGİLİ ÖN HAZIRLIK ÇALIŞMALARI

Hafta	Konular	Ön Hazırlık	Öğrenme Çıktısı
1	Review of Optimization Fundamentals	Lecture Notes	LO1
2	Solution Methods for Large-Scale Integer Programming Problems: Linear Programming Relaxations	Lecture Notes	LO2
3	Solution Methods for Large-Scale Integer Programming Problems: Dantzig&Wolfe Algorithm	Lecture Notes	LO3
4	Solution Methods for Large-Scale Integer Programming Problems: Branch and Bound Algorithm	Lecture Notes	LO3
5	Solution Methods for Large-Scale Integer Programming Problems: Branch and Bound Algorithm	Lecture Notes	LO3
6	Solution Methods for Large-Scale Integer Programming Problems: Lagrangian Relaxation	Lecture Notes	LO3
7	Solution Methods for Large-Scale Integer Programming Problems: Lagrangian Relaxation	Lecture Notes	LO3
8	Midterm Exam		-
9	Solution Methods for Large-Scale Integer Programming Problems: Branch and Cut Algorithm	Lecture Notes	LO3
10	Solution Methods for Large-Scale Integer Programming Problems: Cutting Plane Algorithm	Lecture Notes	LO3
11	Solution Methods for Large-Scale Integer Programming Problems: Benders Decomposition	Lecture Notes	LO4
12	Midterm		-
13	Dynamic Programming	Lecture Notes	LO4
14	Dynamic Programming	Lecture Notes	LO4
15	Review		-
16	Final Exam		-

Ders Kitabı	Wolsey L. A. and Nemhauser G. L. (2014). Integer and combinatorial optimization. John Wiley and Sons.
Önerilen Okumalar/Materyaller	Martin R. K. (2012) Large scale linear and integer optimization a unified approach. Springer Science and Business Media.

DEĞERLENDİRME ÖLÇÜTLERİ

Yarıyıl Aktiviteleri	Sayı	Katkı Payı %	LO1	LO2	LO3	LO4
Ara Sınav	2	60	X	X	X	X
Final Sınavı	1	40	X	X	X	X
Toplam	3	100

AKTS / İŞ YÜKÜ TABLOSU

Yarıyıl Aktiviteleri	Sayı	Süre (Saat)	İş Yükü
Katılım	-	-	-
Teorik Ders Saati	16	3	48
Laboratuvar / Uygulama Ders Saati	14	4	56
Sınıf Dışı Ders Çalışması	-	-	-
Arazi Çalışması	-	-	-
Küçük Sınav / Stüdyo Kritiği	-	-	-
Portfolyo	-	-	-
Ödev	-	-	-
Sunum / Jüri Önünde Sunum	-	-	-
Proje	-	-	-
Seminer/Çalıştay	-	-	-
Sözlü Sınav	-	-	-
Ara Sınavlar	2	22	44
Final Sınavı	1	32	32
		Toplam	180

DERSİN ÖĞRENME ÇIKTILARININ PROGRAM YETERLİLİKLERİ İLE İLİŞKİSİ

#	PC Alt	Program Yeterlilikleri / Çıktıları	* Katkı Düzeyi
#	PC Alt	Program Yeterlilikleri / Çıktıları	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computation, and related engineering discipline-specific topics; the ability to apply this knowledge to solve complex engineering problems.
	1	Mathematics
	2	Science
	3	Basic Engineering
	4	Computation
	5	Related engineering discipline-specific topics			LO1
	6	The ability to apply this knowledge to solve complex engineering problems
2	Problem Analysis: Ability to identify, formulate and analyze complex engineering problems using basic knowledge of science, mathematics and engineering, and considering the UN Sustainable Development Goals relevant to the problem being addressed.
3	Engineering Design: The ability to devise creative solutions to complex engineering problems; the ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions.
	1	Ability to design creative solutions to complex engineering problems
	2	Ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions
4	Use of Techniques and Tools: Ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while recognizing their limitations.					LO2 LO3 LO4
5	Research and Investigation: Ability to use research methods to investigate complex engineering problems, including literature research, designing and conducting experiments, collecting data, and analyzing and interpreting results.
	1	Literature research for the study of complex engineering problems
	2	Designing experiments
	3	Ability to use research methods, including conducting experiments, collecting data. analyzing and interpreting results
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals; awareness of the legal implications of engineering solutions.
	1	Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals
	2	Awareness of the legal implications of engineering solutions
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility; awareness of being impartial, without discrimination, and being inclusive of diversity.
	1	Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility ethical responsibility
	2	Awareness of being impartial and inclusive of diversity, without discriminating on any subject
8	Individual and Teamwork: Ability to work effectively, individually and as a team member or leader on interdisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
	1	Ability to work individually and within the discipline
	2	Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote or hybrid)
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession) on technical issues.
	1	Ability to communicate verbally
	2	Ability to communicate effectively in writing
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
	1	Knowledge of business practices such as project management and economic feasibility analysis
	2	Awareness of entrepreneurship and innovation
11	Lifelong Learning: Lifelong learning skills that include being able to learn independently and continuously, adapting to new and developing technologies, and thinking questioningly about technological changes.