ECTS - Quantitative Analysis and Introduction to Modeling

Quantitative Analysis and Introduction to Modeling (IE122) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Quantitative Analysis and Introduction to Modeling IE122 2 0 0 2 3
Pre-requisite Course(s)
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer.
Course Coordinator
Course Lecturer(s)
  • Dr. Öğr. Üyesi Fatma YERLİKAYA ÖZKURT
Course Assistants
Course Objectives The objective of this course is to introduce the concept of optimization and basic quantitative techniques in industrial engineering.
Course Learning Outcomes The students who succeeded in this course;
  • Students will be able to develop an understanding of the concept of optimization.
  • Students will be able to differentiate deterministic and stochastic models.
  • Students will be able to differentiate exact and approximate solutions of optimization problems.
  • Students will understand the concept of simulation.
Course Content Optimization, classification of optimization problems, exact and approximate solutions, simulation.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 The concept of optimization Chapter 14
2 Optimization problems and their classification Chapter 14
3 Linear programming Chapter 14
4 Examples on mathematical formulation of optimization problems Chapter 14
5 Techniques for solving optimization problems Chapter 14
6 Midterm
7 Probabilistic models Chapter 15
8 Decision Analysis and Decision Trees Chapter 15
9 Examples form Queuing theory Chapter 15
10 Examples from Inventory control Chapter 15
11 Examples from transportation and network models Chapter 5
12 Simulation Chapter 16
13 Project Management Chapter 17
14 Working under uncertainty: systems analysis and design Chapter 18
15 Case Examples and Discussions Supplementary Sources
16 Final Exam


Course Book 1. [1] W.C. Turner, J.H. Mize, K.E. Case, and J.W. Nazametz, Introduction to Industrial & Systems Engineering (3rd ed.), Prentice Hall, 1993.
Other Sources 2. Gerekli oldukça çeşitli kaynaklardan okuma materyali.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics 2 20
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 50
Toplam 4 100
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science and engineering to Industrial Engineering; an ability to apply theoretical and practical knowledge to model and solve engineering problems. X
2 An ability to identify, formulate and solve complex engineering problems; an ability to select and apply proper analysis and modeling methods. X
3 An ability to design a complex system, process, tool or component to meet desired needs within realistic constraints; an ability to apply modern design.
4 An ability to develop, select and put into practice techniques, skills and modern engineering tools necessary for engineering practice; an ability to use information technology effectively. X
5 An ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or disciplinary research topics.
6 An ability to work individually, on teams, and/or on multidisciplinary teams.
7 Ability to communicate effectively in Turkish orally and in writing; knowledge of at least one foreign language; effective report writing and understand written reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instruction.
8 A recognition of the need for, and an ability to engage in life-long learning; an ability to use information-seeking tools and to follow the improvements in science and technology.
9 An ability to behave according to the ethical principles, an understanding of professional and ethical responsibility. Information on standards used in industrial engineering applications.
10 Knowledge of business applications such as project management, risk management and change management. A recognition of entrepreneurship, innovativeness. Knowledge of sustainable improvement. X
11 Information on the effects of industrial engineering practices on health, environment and security in universal and societal dimensions and the information on the problems of the in the field of engineering of the era. Awareness of the legal consequences of engineering solutions.
12 An ability to design, development, implementation and improvement of integrated systems that include human, materials, information, equipment and energy.
13 Knowlede on appropriate analytical, computational and experimental methods to provide system integration.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 2 32
Special Course Internship
Field Work
Study Hours Out of Class 14 1 14
Presentation/Seminar Prepration
Homework Assignments
Quizzes/Studio Critics 2 9 18
Prepration of Midterm Exams/Midterm Jury 1 12 12
Prepration of Final Exams/Final Jury 1 12 12
Total Workload 88