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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| STATISTICS (MASTER) (WITH THESIS) | |
| Code | ISB572 |
| Name | Mathematical Modeling and Applications in Operations Research |
| Term | 2026-2027 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. NİMET ÖZBAY |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The objective of this course is to provide detailed information on mathematical modeling and solution techniques in operations research and to develop the ability of applying these techniques through software-supported examples.
Course Content
This course covers the following topics: Modeling Approach in Operations Research, Linear Programming, Transportation and Assignment Problems, Network Optimization Models, Nonlinear Programming, Formulation of Various Problems, Solving Models, Software-Supported Examples.
Course Precondition
None
Resources
Hillier, F. S. (2005). Introduction to operations research. McGrawHill.
Notes
Winston, W. L. (2004). Operations research: applications and algorithms. Thomson Learning, Inc..
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Develops a mathematical model of a problem in operations research |
| LO02 | Uses the appropriate optimization method for the problem |
| LO03 | Solves the linear programming models |
| LO04 | Explains transportation and assignment models and solves related examples |
| LO05 | Defines network optimization models and solves relevant examples |
| LO06 | Solves nonlinear programming models |
| LO07 | Gains the ability to use various software applications |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Have in-depth theoretical and practical knowledge about Probability and Statistics | |
| PLO02 | Bilgi - Kuramsal, Olgusal | They have the knowledge to make doctoral plans in the field of statistics. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Has comprehensive knowledge about analysis and modeling methods used in statistics. | 4 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Has comprehensive knowledge of methods used in statistics. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Make scientific research on Mathematics, Probability and Statistics. | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Indicates statistical problems, develops methods to solve. | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply innovative methods to analyze statistical problems. | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Designs and applies the problems faced in the field of analytical modeling and experimental researches. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Access to information and do research about the source. | 3 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Develops solution approaches in complex situations and takes responsibility. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Has the confidence to take responsibility. | |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | They demonstrate being aware of the new and developing practices. | |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | He/She constantly renews himself/herself in statistics and related fields. | |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Communicate in Turkish and English verbally and in writing. | 2 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Transmits the processes and results of their studies clearly in written and oral form in national and international environments. | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | It considers the social, scientific and ethical values in the collection, processing, use, interpretation and announcement stages of data and in all professional activities. | |
| PLO17 | Yetkinlikler - Öğrenme Yetkinliği | Uses the hardware and software required for statistical applications. | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Defining the problem | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım |
| 2 | Formulating the mathematical model | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 3 | Linear programming model | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 4 | Linear programming and its applications | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Problem Çözme, Bireysel Çalışma |
| 5 | Software-supported examples for linear programming models | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Bireysel Çalışma |
| 6 | Transportation model and its applications | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 7 | Software-supported examples for transportation model | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Bireysel Çalışma |
| 8 | Mid-Term Exam | Review of the topics using lecture notes and source materials | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Assignment model and its applications | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 10 | Software-supported examples for assignment model | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Bireysel Çalışma |
| 11 | Network optimization models | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 12 | Network optimization models and its applications | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 13 | Software-supported examples for network optimization models | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Bireysel Çalışma |
| 14 | Nonlinear programming and its applications | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 15 | Software-supported examples for nonlinear programming models | Conducting preliminary research on the subject and investigating current applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Bireysel Çalışma |
| 16 | Term Exams | Review of the topics using lecture notes and source materials | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Review of the topics using lecture notes and source materials | Ölçme Yöntemleri: Yazılı Sınav |
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 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||