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)
(IE201 veya MATH392)

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
#	Program Qualifications / Competencies	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