INDUSTRIAL ENGINEERING (ENGLISH, THESIS)
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 8
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Must Course
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi TUĞCAN DEMİR
Course Lecturer(s): Assoc. Prof. SEROL BULKAN
Dr. Öğr. Üyesi YÜCEL BATU SALMAN
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

Sources

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
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
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) Process view and analytic thinking
2) managerial thinking with technical background
3) To have theoretical knowledge on operations research.
4) Awareness about the applications of operations research
5) To have ability of selection and efficient use of modern techniques, equipments and information technologies for industrial engineering
6) To be capable of designing and conducting experiments and collecting data, analyzing and interpreting results
7) To have verbal and oral effective communication skills by using visual methods in Turkish and English
8) To be aware of entrepreneurship, sustainability and innovation
9) To lead disciplinary and multi-disciplinary teams, to develop solution approaches in complex situations, to work individually and to take responsibility.
10) To have conscious of professional and ethical responsibility
11) To have conscious of necessity to lifelong learning
12) To be aware of economic and legal implications of engineering solutions
13) Economic, social and environmental responsibility while solving management problems