At the end of the course the student:
- is able to formulate an LP- or ILP-model for a given business case (which allows a corresponding model);
- is able to solve (I)LP problems using a software package and to critically evaluate their outcomes;
- has knowledge of and insight in the role of inventories in organizations, and can apply (simple) quantitative techniques for inventory optimization in case demand is deterministic as well as stochastic;
- has knowledge of and insight in queuing models and their behavior and is able to model an appropriate problem as a queuing model and to calculate relevant performance indicators like average queue length, and average waiting and sojourn time;
- understands the idea behind dynamic programming and can model simple problems as DP models and solve these;
- is able to understand the core principles of discrete event simulation;
- is able to design and implement a conceptual simulation model in a simulation environment;
- is able to define input for a simulation model and design experiments;
- is able to perform simulation experiments, interpret the outcomes of the simulation, and formulate recommendations that are useful for the problem owner.
Operations research (OR) is a scientific approach that applies quantitative modeling to solve business problems. In this course a number of OR methods is considered that can be applied to model and solve problems in the areas of production and logistics. The course gives an introduction in these areas and in OR techniques. During the course students get the opportunity to practice the art of OR modeling, to solve the models using computer packages and to critically evaluate the solution. Special attention is being paid to linear models (LP- and ILP-models) that play an important role in aggregated planning problems and to building simulation models. Managing inventories in a company is an important topic. On the one hand inventories are necessary for smoothing operations, but on the other hand they cost a lot of money. A number of different methods to minimize inventory costs are considered. The next topic we discuss is queuing, which plays a crucial role in production as well as service organizations. In service organizations building up inventories to match supply and demand is not possible. Moreover, although you may know average demand for service, uncertainty in customer arrivals and different customer service needs may cause waiting lines (e.g. at cash counters or in the emergency room). Waiting times can also occur in manufacturing due to e.g. natural variation in service times or breakdowns of machines or unavailability of raw materials. Finally, some attention is being paid to dynamic programming, an optimization technique that can be used to turn large unwieldy problems in series of smaller and more tractable problems.