Stochastic Models (IE324) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Stochastic Models IE324 6. Semester 3 0 0 3 6
Pre-requisite Course(s)
IE 201
Course Language English
Course Type Compulsory Departmental Courses
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

Sources

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 Acquires sufficient knowledge in mathematics, natural sciences, and related engineering disciplines; gains the ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. X
2 Gains the ability to identify, define, formulate, and solve complex engineering problems; acquires the skill to select and apply appropriate analysis and modeling methods for this purpose. X
3 Gains the ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions, and applies modern design methods for this purpose.
4 Develops the skills to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in industrial engineering applications; gains the ability to effectively use information technologies.
5 Gains the ability to design experiments, conduct experiments, collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.
6 Acquires the ability to work effectively in intra-disciplinary and multidisciplinary teams, as well as individual work skills.
7 Acquires effective oral and written communication skills in Turkish; at least one foreign language proficiency; gains the ability to write effective reports, understand written reports, prepare design and production reports, make effective presentations, and give and receive clear instructions.
8 Develops awareness of the necessity of lifelong learning; gains the ability to access information, follow developments in science and technology, and continuously renew oneself.
9 Acquires the consciousness of adhering to ethical principles, and gains professional and ethical responsibility awareness. Gains knowledge about the standards used in industrial engineering applications.
10 Gains knowledge about practices in the business life such as project management, risk management, and change management. Develops awareness about entrepreneurship and innovation. Gains knowledge about sustainable development.
11 Gains knowledge about the universal and social dimensions of the impacts of industrial engineering applications on health, environment, and safety, as well as the problems reflected in the engineering field of the era. Gains awareness of the legal consequences of engineering solutions.
12 Gains skills in the design, development, implementation, and improvement of integrated systems involving human, material, information, equipment, and energy.
13 Gains knowledge about appropriate analytical and experimental methods, as well as computational methods, for ensuring system integration.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Project 1 16 16
Report
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