Advanced Modeling, Optimization, and Simulation in Operations Management

The acquired skills are used in the field of operations management to understand, redesign, control and optimize the production of goods and services. The students learn quantitative methods for the analysis of decision problems in operations management, and therefore, the basis for all subsequent lectures at the Department of Operations & Supply Chain Management. The presented methods can be subdivided into two distinct study sections: optimization and simulation. Optimization section: - Introduction to linear programming, CPLEX Studio IDE, and IBM ILOG OPL - LP formulations, e.g. production planning problems - Model building with OPL, e.g. generic modeling, model testing with instances, scripting for pre- and post-processing - Interpreting and using the solution of a LP model - Spreadsheet input/output with OPL Simulation section: - Introduction to simulation, AnyLogic - System; event; model; steps in a simulation study - Data collection, statistical analyse and input modeling - Fundamental simulation concepts in AnyLogic - Simulation of simple systems together with verification, calibration, and validation - Statistical simulation data output analysis having regard to different scenarios

At the end of the module, students will be able to create mixed integer linear programming formulations, and discrete event simulation models of simple problems in production and operations management. Furthermore, students will be able to solve MILP formulations in OPL and IBM ILOG Script, and implement discrete event simulation models in AnyLogic. The students also learn, how to evaluate and compare the calculated problem solutions.

The offered module is composed of the sections optimization and simulation. In both sections, basic knowledge and skills for designing and evaluating service and production processes are taught. The solution of analyzed problems is gained either through the application of optimization methods or through simulation. Due to the different problem-solving approaches (and the use of different software packages), both sections are thought separately. To facilitate the learning success, the learning outcomes are examined directly at the end of each section. At the end of the optimization section, there is a written exam on modeling linear optimization problems. In addition to theoretical knowledge, the students' skills in modeling with OPL and IBM ILOG CPLEX are tested. At the end of the simulation section, there is also a written exam, in which the learning outcomes in discrete-event simulation, using the software AnyLogic are tested. Both exams evaluate the individual performance of the acquired theoretical and practical skills, requiring own calculations and argumentative answers. Exams are worth 60 points each and noncumulative. To pass the course, students need to pass both exams individually. The final grade of the module is the truncated average of the exam grades. Both exams take 60 minutes each. In the exams, no aids are allowed. In addition, students can achieve a 0.3/0.4-grade bonus (according to APSO/ FPSO midterm) in each section through the successful participation in the respective homework assignments.

Management Science, Basic course in Statistics, Basic Couse in Mathematics, Production and Logistics

The weekly sessions consist of a lecture with an integrated exercise class. During the lecture, the content is presented and discussed. The students are invited to improve the acquired knowledge by studying the suggested literature. In the exercise, the students apply the acquired knowledge by solving and implementing given problems. The homework assignments allow students to individually improve their skills, by answering theoretical questions and implementing problems, using the respective software. After each homework assignment, the students are free to discuss their solutions and open questions in a Q&A session.