The course provides an introduction to the theoretical aspects and practical adaptation of Operations Research methods for modeling and solving linear optimization problems, especially in production, transportation and logistics. Furthermore, elementary concepts of probability as well as discrete and continuous distributions are reviewed and the relevance for basic Operations and Supply Chain Management (OSCM) models is demonstrated.

Topics include:

• Formulation of a linear or integer optimization model
• Basics of the mathematical solution
• Solution using standard software (Excel)
• Sensitivity analysis
• Basics of probability and discrete and continuous random variables
• Single period inventory model with discrete demand distribution
• Capacity management with queuing models: Poisson and exponential distribution
• Demand aggregation (pooling): Sum of Normal distributions

• Formulate a certain class of decision problems as linear or a (mixed) integer programs
• Solve a linear or integer program
• Interpret the optimal solution and perform elementary sensitivity analysis
• Use network planning procedures for solving logistics problems
• Understand and apply elementary probability laws and random variables and their moments (Expectation, standard deviation, coefficient of variation) to OSCM models
• Analyze basic inventory-related performance measures and their relationships (expected sales and lost-sales, cycle service level, fill rate)
• Formulate a queuing model with exponential processing times and Poisson demand and to derive the expected waiting time, cycle time and work in progress (WIP)
• Understand the independence and correlation of random variables and their impact on centralization of demands of products or locations (Example: Normal distribution)

Attendance requirement is met if a student is present for at least 80% of the lectures.

The course is taught using a combination of lectures, class discussions,homework exercises and in-class assignments.

The main topics will be presented in class. You will be required to do homework exercises and in-class assignments.

Assessment

• Homework exercises, 30 points (6 homeworks)
• In-class assignments, 20 points (4 assignments)
• Final exam, 50points: Min. 20 points out of 50 are required for passing the course

Grading scale:

•     Excellent (1): 90% - 100.0%

•     Good (2): 80% - <90%

•     Satisfactory (3): 70% - <80%

•     Sufficient (4): 60.0% - <70%

•     Fail (5): <60.0%

Prerequisite for passing the course: minimum performance of 40% in the final examination.

Incoming students (exchange programs): tba

Werner.jammernegg@wu.ac.at, belma.turan@wu.ac.at

Tutor: Anna Floßmann    Email: anna.flossmann@wu.ac.at

Program's website: www.wu.ac.at/master/scm