Queueing Theory (MAE634): Διαφορά μεταξύ των αναθεωρήσεων

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(Νέα σελίδα με '=== General === {| class="wikitable" |- ! 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 Off...')
 
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=== Attached Bibliography ===
=== Attached Bibliography ===
Bibliography
* Φακίνος, Δ. Στοχαστικά Μοντέλα στην Επιχειρησιακή Έρευνα, Σ. Αθανασόπουλος-Σ. Παπαδάμης & ΣΙΑ, Αθήνα, 2003.
* Φακίνος, Δ. Στοχαστικά Μοντέλα στην Επιχειρησιακή Έρευνα, Σ. Αθανασόπουλος-Σ. Παπαδάμης & ΣΙΑ, Αθήνα, 2003.
* Hillier F.S. and Lieberman, G.J. Introduction to Operations Research, 7/E. McGraw-Hill, New York, 2000.
* Hillier F.S. and Lieberman, G.J. Introduction to Operations Research, 7/E. McGraw-Hill, New York, 2000.

Αναθεώρηση της 13:14, 29 Ιουνίου 2022

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

Bibliography

  • Φακίνος, Δ. Στοχαστικά Μοντέλα στην Επιχειρησιακή Έρευνα, Σ. Αθανασόπουλος-Σ. Παπαδάμης & ΣΙΑ, Αθήνα, 2003.
  • 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.

Related academic journals:

  • Queueing Systems, Theory and Applications