COURSE UNIT TITLE

Offered By

Business Administration (English)

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR SABRI ERDEM

Offered to

Business Administration (English)

Course Objective

This course aims at gainin the fundamental knowledge and esperience about modeling and analyzing business processes using simulation techniques; providing use of various simulation packages and languages for business analysis; integrating simulation to different decision and forecasting models, i.e., heuristic models, response surface methodology, design ofexperiments).

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

Books:
Ross, S. M. (2012), Simulation, 5th Edition, Academic Press Publication
Banks, J. & Carson II, J. S., 2009, Discrete-Event System Simulation, 5th Edition, Pearson
Law, A. M., (2013), Simulation Modeling and Analysis, 5th Edition, McGraw-Hill
Nelson, B. (2013). Foundations and Methods of Stochastic Simulation. Springer
Jones, O., Maillardet, R., & Robinson, A. (2014). Introduction to Scientific Programming and Simulation Using R. CRC Press.
Grolemund, G. (2014). Hands-On Programming with R: Write Your Own Functions and Simulations. O Reilly.
Matloff, N. (2009). The Art of R Programming. No Starch Press.

MOOCs:
edX Course: Introduction to Computational Thinking and Data Science https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-0 (Simulation with Python)
Coursera Course: R Programming https://www.coursera.org/course/rprog (Simulation with R)

Web Sites:
Simpy Discrete Event Simulation Package documentation: https://simpy.readthedocs.org/en/latest/

Articles:
L'ecuyer, P. (1988). Efficient and portable combined random number generators. Communications of the ACM, 31(6), 742-751.
L'ecuyer, P. (1999). Good parameters and implementations for combined multiple recursive random number generators. Operations Research, 47(1), 159-164.
Box, G. E., & Muller, M. E. (1958). A note on the generation of random normal deviates. The annals of mathematical statistics, (29), 610-611.
Kronmal, R. A., & Peterson Jr, A. V. (1979). On the alias method for generating random variables from a discrete distribution. The American Statistician, 33(4), 214-218.
Brysbaert, M. (1991). Algorithms for randomness in the behavioral sciences: A tutorial. Behavior Research Methods, Instruments, & Computers, 23(1), 45-60.
Charnes, J. M. (1991, December). Multivariate simulation output analysis. In Proceedings of the 23rd conference on Winter simulation (pp. 187-193). IEEE Computer Society.
Chen, E. J., & Kelton, W. D. (2008). Estimating steady-state distributions via simulation-generated histograms. Computers & Operations Research, 35(4), 1003-1016.
Goldsman, D., Kim, S. H., & Nelson, B. (2005, December). Statistical selection of the best system. In Simulation Conference, 2005 Proceedings (pp. 10-pp). IEEE.
Angün, E., Kleijnen, J. P., Hertog, D. D., & Gürkan, G. (2002, December). Recent advances in simulation optimization: response surface methodology revisited. In Proceedings of the 34th conference on Winter simulation: exploring new frontiers (pp. 377-383). Winter Simulation Conference.
Zhou, M. (1998). Modeling, analysis, simulation, scheduling, and control of semiconductor manufacturing systems: A Petri net approach. Semiconductor Manufacturing, IEEE Transactions on, 11(3), 333-357.

Planned Learning Activities and Teaching Methods

Lecture, group work, presentations, class discussions.

Assessment Methods

Further Notes About Assessment Methods

None

Assessment Criteria

1. Midterm Exam
Students will be assessed on their knowledge of concepts and theories through an essay-type written exam. Long text case studies will be handled.
2. Term Project
Groups will do a research in a real business environment about business architectures and models and prepare a written report based on the format given by the instructor. They are expected to share their observation and experience with their class-mates through oral presentations.
3. Class Discussions and Presentation
Students will be given certain cases or questions related to the concepts covered in the class. Groups will debate on the topics and present their opinions. Students are expected to contribute to class discussions.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.
3. Students are expected to participate actively in class discussions.
4. Students are expected to attend to classes on time.
5. Students are expected to prepare ahead of time for class.

Contact Details for the Lecturer(s)

Email: sabri.erdem@deu.edu.tr
Phone: (232) 301 82 57

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes