Optimization and Simulation (BAN 821)

2021 Spring
Sabancı Business School
Business Analytics(BAN)
3
10
Can Akkan canakkan@sabanciuniv.edu,
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English
Doctoral, Master
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CONTENT

This course introduces the basic principles and techniques of mathematical modeling that will aid managerial decisions. Students will learn how to develop analytical models and use techniques such as linear and mixed integer programming, Monte Carlo simulation, discrete-event simulation and decision trees. The applications are on models that are widely used in diverse business functional areas.

LEARNING OUTCOMES

PROGRAMME OUTCOMES


1. Develop the ability to use critical, analytical, and reflective thinking and reasoning 5

2. Reflect on social and ethical responsibilities in his/her professional life. 1

3. Gain experience and confidence in the dissemination of project/research outputs 1

4. Work responsibly and creatively as an individual or as a member or leader of a team and in multidisciplinary environments. 3

5. Communicate effectively by oral, written, graphical and technological means and have competency in English. 4

6. Independently reach and acquire information, and develop appreciation of the need for continuously learning and updating. 1


1. Develop, interpret and use statistical analyses in decision making. 5


1. Demonstrated understanding of data-driven decision modeling and analysis concepts/frameworks. 5

2. Knowledge of and hands-on experience with fundamentals of business analytics, management information systems, statistical and prediction models. 5

3. Ability to transform complex data into valuable insight and resulting value-adding actions. 5

4. Skills in hands-on data-mining tools and techniques. 1

5. Exposure to the analytical methods in basic business disciplines such as marketing, operations, and finance 5