Queueing Theory (MAE634)

Undergraduate Courses Outlines - Department of Mathematics

General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Undergraduate
Course Code	MAE634
Semester	6
Course Title	Queueing Theory
Independent Teaching Activities	Lectures (Weekly Teaching Hours: 3, Credits: 6)
Course Type	Special Background
Prerequisite Courses	-
Language of Instruction and Examinations	Greek
Is the Course Offered to Erasmus Students	Yes
Course Website (URL)	-

Learning Outcomes

Learning outcomes

The course learning outcomes are: the study and development models that describe and analyse the behaviour and performance of queueing systems and their applications for optimal decision making. Upon successful completion of the course the student will be able to: recognize and implement M/M/1 queue model and its variants apply the Little's result recognize and implements M/G/1 queue model apply Markov processes to model queueing systems apply queueing models for decision making.

General Competences

Working independently Decision-making Adapting to new situations Production of free, creative and inductive thinking Synthesis of data and information, with the use of the necessary technology.

Syllabus

Introduction. Birth death process. Transforms. Markovian Queueing Systems (Μ/Μ/1/∞, Μ/Μ/m/k, Μ/Μ/m/m, Μ/Μ/∞/∞). Queue with group arrival, Queue with group services, M/G/1/∞. Applications for optimal decision making.

Teaching and Learning Methods - Evaluation

Delivery	Face-to-face
Use of Information and Communications Technology	- Software for the calculation of queueing systems performance measures, Email, class web
Teaching Methods	Activity Semester Workload Lectures 39 Independent study 78 Fieldwork (3-4 set of homework) 33 Course total 150
Student Performance Evaluation	LANGUAGE OF EVALUATION: Greek METHODS OF EVALUATION: Final exam (100%)

Attached Bibliography

See the official Eudoxus site or the local repository of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Additionally:

• Hillier F.S. and Lieberman, G.J. Introduction to Operations Research, 7/E. McGraw-Hill, New York, 2000.
• Taha, H.A. Operations Research: An Introduction, 9/E. Prentice Hall, Englewood Cliffs, NJ, 2011.
• Ross, S.M. Introduction to Probability Models, 9/E. Academic Press, Amsterdam 2007.
• Journal: Queueing Systems, Theory and Applications