Stochastic Models (IE324) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Stochastic Models IE324 3 0 0 3 6
Pre-requisite Course(s)
IE 201
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, Problem Solving.
Course Coordinator
Course Lecturer(s)
  • Dr. Öğr. Üyesi Kamil Demirberk ÜNLÜ
Course Assistants
Course Objectives To prepare the student to model and analyze complex systems through the application of probabilistic techniques such as Markov Chains, and queuing analysis.
Course Learning Outcomes The students who succeeded in this course;
  • Ability to develop skills in building stochastic models using Markov chains.
  • Ability to better understand inventory/production control in light of stochastic models.
  • To develop an understanding of queuing systems under different configurations.
Course Content The definition and classification of stochastic processes, Markov chains, queueing systems, stochastic inventory models.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 The concepts of stochastic event, process and system
2 Review of Probability
3 Definition and classification of stochastic processes
4 Markov chains: Definitions
5 Markov chains: Problem Formulation
6 Markov chains: Applications in inventory models
7 Poisson process
8 Continuous time Markov chains
9 Midterm
10 Birth and Death processes
11 Queueing systems: Modeling
12 Queueing systems: Analysis
13 Simulation of stochastic processes
14 Stochastic optimization models
15 Final Examination Period
16 Final Examination Period


Course Book 1. Introduction to Probability Models, Sheldon M. Ross, Academic Press.
Other Sources 2. Fundamentals of Queuing Theory, Gross, D. and Harris, C.M., Wiley.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project 1 15
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 50
Toplam 3 100
Percentage of Semester Work 50
Percentage of Final Work 50
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.
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.
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 3 48
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Project 1 16 16
Homework Assignments
Quizzes/Studio Critics 2 2 4
Prepration of Midterm Exams/Midterm Jury 1 8 8
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 150