Operations Research II

Course Code:

ISE 323

Course Period:

Autumn

Course Type:

Core

Credits:

4

Theoric:

3

Practice:

2

Laboratory Hour:

0

ECTS:

7

Prerequisite Courses:

Probability

Statistical Applications for Industrial Engineers

Course Language:

English

Courses given by:

Melek Başak

Course Objectives:

• Utilize the basic probability concepts in Markovian probabilistic frame. • Develop intuition in capturing the underlying probabilistic structure. • Develop model building skills related to the topics covered. • Understand and apply the concept of conditioning in probability. • Understand the Markovian property, recognize and model Markov chains in various application problems. • Remember and enlarge the properties of Poisson distribution, exponential distribution, gamma Distribution and understand the relationship among them. • Learn the basics principles of queuing theory. - Study M/M/1 queuing models in detail. • Develop modelling skills with the help of some more complex queuing examples.

Course Content:

1. Basics of Probability Theory

2. Markov Chains

3. Poisson Process and Exponential Distribution

4. Queueing Theory

Course Methodology:

1: Lecture by instructor, 2: Lecture by instructor with class discussion, 3: Problem solving by instructor,,

Course Evaluation Methods:

A: Written exam, B: Multiple-choice exam C: Take-home quiz, D: Experiment report, E: Homework, F: Project, G: Presentation by student, H: …

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Course Learning Outcomes

Course Learning Outcomes	Detailed Program Outcomes	Teaching Methods	Assessment Methods
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems.	1a, 1b, 2a, 2b, 6c	1, 2, 3	A, C, E, F
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.	1a, 1b, 2a, 2b, 6c	1, 2, 3	A, C, E, F
Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice	6c	12	H

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	Probability Theory Review: Random experiment, Axioms of probability Conditional Probability, Independence	Textbooks, Course Notes
2	Probability Theory Review: Discrete random variables Continuous random variables	Textbooks, Course Notes
3	Probability Theory Review: Expectation, Jointly distributed random variables	Textbooks, Course Notes
4	Probability Theory Review: Independent random variables, Covariance and Correlation, Conditional Probability, Computing Expectations and Probabilities by conditioning	Textbooks, Course Notes
5	Markov Chains: Introduction, Markov Chains: ChapmanKolmogorov Equations, States	Textbooks, Course Notes
6	Markov Chains: Chapman-Kolmogorov Equations, States, Steady State probabilities	Textbooks, Course Notes
7	Markov Chains: Steady State probabilities Applications.	Textbooks, Course Notes
8	Markov Chains: Steady State probabilities Applications	Textbooks, Course Notes
9	Markov Chains, Absorbing Markov Chains, Stationary distributions, Absorbing chains Work Force planning	Textbooks, Course Notes
10	The Exponential Distribution & Poisson Processes: Counting processes	Textbooks, Course Notes
11	Exponential Distribution & Poisson Processes: Poisson Processes, Generalized Poisson processes	Textbooks, Course Notes
12	Queueing Theory: Basics and Exponential Queuing Models	Textbooks, Course Notes
13	Queueing Theory: Basics and Exponential Queuing Models	Textbooks, Course Notes
14	Queueing Theory: Exponential Queueing Models, infinite and finite capacity models, open networks	Textbooks, Course Notes

Recommended Sources

RECOMMENDED SOURCES

Textbook

Int. to Probability Models

Sheldon M. Ross

Additional Resources

Operations Research: Applications and Algorithms

W. L. Winston, Thompson –

Brooks/Cole, 2004

Material Sharing

MATERIAL SHARING
Documents	Lecture notes, lab notes, https://coadsys.yeditepe.edu.tr/
Assignments	Quizzes
Exams	Midterm exams, final exam

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE
Midterm	2	40
Quiz	2	20
Total		60
Contribution of final examination to overall grade		40
Contribution of in-term studies to overall grade		60
Total		100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM OUTCOMES
No	Program Learning Outcomes	check X
1a	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline,	X
1b	Ability to use theoretical and applied knowledge in these areas in complex engineering problems.	X
2a	Ability to identify, formulate, and solve complex engineering problems,	X
2b	Ability to select and apply proper analysis and modeling methods for this purpose.	X
3a	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result,
3b	Ability to apply modern design methods for this purpose.
4a	Ability to devise, select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice.
4b	Ability to employ information technologies effectively.
5a	Ability to design experiments for investigating complex engineering problems or discipline specific research questions,
5b	Ability to conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6a	Ability to work efficiently in intra-disciplinary teams,
6b	Ability to work efficiently in multi-disciplinary teams,
6c	Ability to work individually.	X
7a	Ability to communicate effectively both orally and in writing,
7b	Knowledge of a minimum of one foreign language,
7c	Ability to write effective reports and comprehend written reports, prepare design and production reports,
7d	Ability to make effective presentations,
7e	Ability to give and receive clear and intelligible instructions.
8a	Recognition of the need for lifelong learning, ability to access information, ability to follow developments in science and technology,
8b	Ability to continue to educate him/herself.
9a	Consciousness to behave according to ethical principles and professional and ethical responsibility.
9b	Knowledge on standards used in engineering practice.
10a	Knowledge about business life practices such as project management, risk management, change management.
10b	Awareness in entrepreneurship and innovation.
10c	Knowledge about sustainable development.
11a	Knowledge about the global and social effects of engineering practices on health, environment, and safety,
11b	Knowledge about contemporary issues of the century reflected into the field of engineering.
11c	Awareness of the legal consequences of engineering solutions.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration	14	3	42
Laboratory	12	2	24
Hours for off-the-classroom study (Pre-study, practice)	14	5	70
Midterm	2	2	4
Quiz	2	4	8
Final	1	2	2
Total Work Load			150
Total Work Load / 25 (h)			6
ECTS Credit of the Course			7

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