TÜRKÇE
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Information
| Unit | FACULTY OF ENGINEERING |
| INDUSTRIAL ENGINEERING PR. | |
| Code | ENM210 |
| Name | Introduction to Modeling and Optimization |
| Term | 2025-2026 Academic Year |
| Semester | 4. Semester |
| Duration (T+A) | 2-1 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 2.5 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. YUSUF KUVVETLİ |
| Course Instructor |
The current term course schedule has not been prepared yet. Previous term groups and teaching staff are shown.
|
Course Goal / Objective
To Define industrial problems and optimize them by using mathematical modelling techniques
Course Content
Identification of industrial problems, establishment of metamatic models, optimum solution derivation and sensitivity analysis by existing computer package programs to established models.
Course Precondition
None
Resources
Esin, A. & Şahin S.T. (2012). Yöneylem Araştırmasında Yararlanılan Karar Yöntemleri. 5. Baskı, Gazi Kitabevi, ISBN: 978-975-8640-79-9.
Notes
Taha, H. A. (2010). Yöneylem Araştırması, Çev. Baray, ŞA ve Esnaf Ş., Literatür Yayınları, 43, 905. Öztürk, A. (2015). Yöneylem araştırmasına giriş. Ekin Basım Yayın Dağıtım. Winston, W. L., & Goldberg, J. B. (2004). Operations research: applications and algorithms (Vol. 3). Belmont^ eCalif Calif: Thomson/Brooks/Cole.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Identification of optimization problems |
| LO02 | Verbal description of the problem |
| LO03 | Construct the mathematical model |
| LO04 | Graphical solution of mathematical models |
| LO05 | Graphical solution method to nonlinearl programming models |
| LO06 | Model building and solution derivation in LINGO package program |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Acquires sufficient knowledge in mathematics, science and Industrial Engineering discipline-specific subjects; acquires the ability to use theoretical and applied knowledge in these fields in complex engineering problems. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Acquires the ability to identify, define, formulate and analytically solve complex Industrial Engineering problems; and has the ability to select and apply appropriate analysis and modelling methods for this purpose. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Acquires the ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; acquires the ability to apply modern design methods for this purpose. | 5 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Acquires the ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in Industrial Engineering applications and acquires the ability to use information technologies effectively. | 3 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Acquire the skills to design and conduct experiments, collect data, analyze and interpret results to investigate complex Industrial Engineering problems or discipline-specific research topics. | 4 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Have the ability to work effectively in disciplinary and multi-disciplinary teams or individually. | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Ability to communicate effectively in Turkish, both verbally and in writing; knowledge of at least one foreign language; ability to write and understand effective reports, prepare design and production reports, make effective presentations, and give and receive clear and understandable instructions. | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | They have awareness of the necessity of lifelong learning; they have the ability to access information, follow developments in science and technology, and constantly renew themselves. | |
| PLO09 | Yetkinlikler - Öğrenme Yetkinliği | Acting in accordance with ethical principles, becoming knowledgeable about the standards used in engineering practices with awareness of professional and ethical responsibility. | |
| PLO10 | Yetkinlikler - Öğrenme Yetkinliği | Learn about business practices such as project management, risk management and change management, and is aware of entrepreneurship and innovation. | |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Informed about the universal and societal impacts of engineering practices on health, environment and safety, and the contemporary problems reflected in the field of engineering, and is aware of the legal consequences of engineering solutions. | |
| PLO12 | Yetkinlikler - Öğrenme Yetkinliği | Benefit from the power of effective communication in professional life and has the ability to interpret developments correctly. | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Have the ability to design, develop, implement and improve integrated systems that include machines, people, time, information or money. | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | By applying modern design methods, they have the ability to design, develop, implement and improve complex products, processes, businesses and systems under realistic conditions and constraints such as cost, environment, sustainable development, energy, manufacturability, ethics, health, safety and political issues. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | What is optimization | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Beyin Fırtınası, Örnek Olay |
| 2 | Identification of optimization problems | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 3 | Verbal description of the problem | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
| 4 | Construct the mathematical model | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Alıştırma ve Uygulama |
| 5 | Graphical solution of mathematical models | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Örnek Olay, Problem Çözme |
| 6 | Linear programming (introduction) | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Soru-Cevap |
| 7 | Linear programming | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Soru-Cevap |
| 8 | Mid-Term Exam | Study for exam | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Simplex method | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Tartışma |
| 10 | Dual simplex method | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
| 11 | Big-M method | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
| 12 | Sensitivity analysis | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
| 13 | Model building and solution derivation in LINGO package program | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 14 | Sensitivity analysis in LINGO program | Reading lecture notes and references about the subject | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 15 | Sample optimization applications | To find optimum solutions for industrial application problems | Öğretim Yöntemleri: Örnek Olay |
| 16 | Term Exams | Study for exam | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Study for exam | Ölçme Yöntemleri: Yazılı Sınav |
Assessment (Exam) Methods and Criteria
Current term shares have not yet been determined. Shares of the previous term are shown.
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 75 | 30 |
| 1. Performance Task (Application) | 25 | 10 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 2 | 2 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 7 | 7 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 111 | ||
| Total Workload / 25 (h) | 4,44 | ||
| ECTS | 4 ECTS | ||