Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
INE5111 Mathematical Programming and Modelling Fall 3 0 3 6
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi TUĞCAN DEMİR
Course Lecturer(s): Assoc. Prof. SEROL BULKAN
Course Objectives: This course aims to introduce students modeling of linear and integer programs, network flow problems and nonlinear programs; to use the simplex algorithm for solving liner programming problems, branch&bound for solving integer programming problems and some solution algorithms for network flow problems; to understand important modeling techniques and solution algorithms; to get insights about graph theory and its applications; and to identify the types of problems and their solution algorithms.

Learning Outputs

The students who have succeeded in this course;
I. Formulate large-scale problems as an LP, IP or NLP.
II. Identify the type of problems such as linear, integer and nonlinear problems.
III. Analyze the algorithms such as simplex and branch and bound.
IV. Formulate network flow problems and to solve using specially structured algorithms.

Course Content

This course emphasizes modeling of problems as linear programs, mixed integer linear programs, nonlinear programs and network flow programs. In the second half of the course some basic solution algorithms such as simplex and branch and bound, and some network flow programming algorithms are covered.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Linear programming models I
2) Linear programming models II
3) Graphical solution approach and Introduction to Simplex Algorithm
4) Simplex Algorithm
5) Integer programming models I
6) Integer programming models II
7) Branch and Bound Algorithm
8) Midterm 1
9) Nonlinear programming models
10) Network flow programming models I
11) Network flow programming models II
12) Network flow algorithms I
13) Network flow algorithms II
14) Midterm II


Course Notes: N.A.
References: Various reference books will be available at the library.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance % 0
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments 4 % 20
Presentation % 0
Project % 0
Seminar % 0
Midterms 2 % 40
Preliminary Jury % 0
Final 1 % 40
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 12 3 36
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 3 25 75
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 4 18 72
Quizzes 0 0 0
Preliminary Jury 0
Midterms 2 3 6
Paper Submission 0
Jury 0
Final 1 3 3
Total Workload 192

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
Program Outcomes Level of Contribution
1) Have sufficient theoretical background in mathematics, basic sciences and other related engineering areas and to be able to use this background in the field of energy systems engineering.
2) Be able to identify, formulate and solve energy systems engineering-related problems by using state-of-the-art methods, techniques and equipment.
3) Be able to design and do simulation and/or experiment, collect and analyze data and interpret the results.
4) Be able to access information, to do research and use databases and other information sources.
5) Have an aptitude, capability and inclination for life-long learning.
6) Be able to take responsibility for him/herself and for colleagues and employees to solve unpredicted complex problems encountered in practice individually or as a group member.
7) Develop an understanding of professional and ethical responsibility.
8) Develop an ability to apply the fundamentals of engineering mathematics and sciences into the field of energy conversion.
9) Develop an understanding of the obligations for implementing sustainable engineering solutions.
10) Develop an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
11) Realize all steps of a thesis or a project work, such as literature survey, method developing and implementation, classification and discussion of the results, etc.