After successful completion of this module component, the student is able to:
- describe the different types of simulation, their applicability, and how to setup a simulation study;
- understand the core principles of discrete event simulation (e.g., the event controller, random numbers, and warm-up period);
- define input for a simulation model (e.g., different statistical distributions) and design experiments (selection of the type of simulation, warm-up period, replications, combination of experimental factors, ranges, performance indicators, etc.);
- explain the concepts of (i) construction and improvement heuristics and (ii) local search heuristics.
In the module component Simulation and Heuristics, students learn how to perform a simulation study and learn basic heuristic approaches for routing and scheduling. Regarding simulation, the goal is to learn about the principles of discrete event stochastic simulation to be able to conduct a simulation study focused on the improvement of business processes. Regarding heuristics, the goal is to learn how to apply priority rules and sampling to construct solutions, and how to apply local search to improve solutions.