Course Name Code Semester T+U Hours Credit ECTS
Operational Research III (Nonlinear Models) ENM 312 6 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Course Coordinator Dr.Öğr.Üyesi ALPER KİRAZ
Course Lecturers Prof.Dr. HARUN REŞİT YAZĞAN, Doç.Dr. ÖZER UYGUN, Dr.Öğr.Üyesi ALPER KİRAZ,
Course Assistants Res.Asst. Sena Kır, Res.Asst.Alper Kiraz, Res.Asst.Murat Sarı
Course Category
Course Objective Providing students with the basics of modeling and solution techniques
Course Content How can a model can be settled to achieve specified objectives with considering enterprise limited resource constraints and determination of the solution techniques according structure of the model
# Course Learning Outcomes Teaching Methods Assessment Methods
1 An ability of determining the enterprise resources Lecture, Discussion, Drilland Practice, Testing, Homework,
2 Comprehending structure of the linear model Lecture, Question-Answer, Discussion, Drilland Practice, Motivations to Show, Problem Solving, Testing, Homework,
3 Comprehending solution techniques of the linear models Lecture, Question-Answer, Discussion, Drilland Practice, Motivations to Show, Testing, Homework,
4 An ability of determining the optimization problem Lecture, Question-Answer, Discussion, Case Study, Problem Solving, Testing, Homework,
5 An ability of establishing nonlinear model Lecture, Discussion, Drilland Practice, Case Study, Problem Solving, Testing, Homework,
6 Comprehending solution techniques of the nonlinear model Lecture, Question-Answer, Discussion, Case Study, Problem Solving, Testing, Homework,
7 Examples on nonlinear problems Lecture, Question-Answer, Drilland Practice, Case Study, Lab / Workshop, Problem Solving, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Introduction to Non- Linear Models
2 Concav and Convex Functions
3 Newton Method
4 Golden Section Search Metod
5 Gradyan (Steepest Descent ) Metod
6 Lagrange Metod
7 Kuhn-Tucker Conditions
8 Quadratic Programming
9 Separable Programming
10 Midterm Exam
11 Convex Programming(Frank-Wolf Alg.)
12 Non-Convex Programming(Barrier Method-SUMT)
13 Dinamic Programming(Probabilistic)
14 Goal programming
Resources
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. X
2 Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. X
3 Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods. X
4 Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. X
5 Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. X
6 Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually X
7 Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language
8 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology
9 Engineering graduates with well-structured responsibilities in profession and ethics
10 Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development.
11 Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions.
Evaluation System
Semester Studies Contribution Rate
1. Ödev 15
1. Kısa Sınav 15
2. Kısa Sınav 15
1. Ara Sınav 55
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 15 15
Quiz 2 10 20
Assignment 1 10 10
Final examination 1 15 15
Total Workload 156
Total Workload / 25 (Hours) 6.24
dersAKTSKredisi 5