Courses

Our group offers courses for bachelor and master students in information systems, computer science, management, and economics. In particular, the following courses related to decision support and operations research are currently given (further information can be found on the webpage of the University):

Bachelor courses

Decision Support I - Prof. Bernard Ries - Fall semester

Ce cours concerne une introduction à l’aide à la décision par des modèles quantitatifs de recherche opérationnelle. Outre l’exposition des principales méthodes, un accent particulier est mis sur la modélisation et les applications. Divers logiciels sont mis en oeuvre, en particulier le tableur muni de modules add-in. Le cours est structuré de la manière suivante: 
- Aide à la décision et recherche opérationnelle 
- Modèles et méthodes 
- Optimisation linéaire et optimisation linéaire en nombres entiers 
- Modèles de réseaux 

Programmation orientée objet - PD. Dr. Tony Hürlimann - Fall semester

Ce cours est une introduction à la programmation orientée objet en utilisant les concepts du language "Java". Les objectifs du cours sont (1) de comprendre les paradigmes de la programmation orientée objet, (2) maîtriser un langage de programmation orienté objet (Java), et (3) acquérir une bonne méthodologie de programmation. Dans une première partie les fondements et les concepts de la programmation orientée objet sont expliqués: Objets et classes, encapsulation et masquage d'information, sous-classes, héritage, redéfinitions et polymorphisme, interfaces, classes abstraites, paquetages, règles de visibilités. La deuxième partie contient: utilisation de librairies, types génériques, librairies de collections, autres librairies (langage, maths, utilitaires, entrées-sorties, etc.). La troisième partie est destinée à la programmation d'applications interactives, programmation par événements, les librairies AWT, Java2D et Swing, lambda expressions, introduction à la programmation "multi-threads". 

Decision Support II (deutsch) - Spring semester

Inhalt der Lehrveranstaltung sind quantitative Methoden des Operations Research zur Entscheidungsunterstützung. Im ersten Teil werden Algorithmen zur Optimierung in Graphen und Netzwerken (Fluss-Probleme, Minimalgerüste, Kürzeste Wege, Zeitplanung in Projektnetzwerken) behandelt. Im zweiten Teil erfolgt eine Einführung in die Gemischt-Ganzzahlige Optimierung und die Kombinatorische Optimierung anhand verschiedener Beispiele einschliesslich des Handlungsreisendenproblems. Im dritten Teil werden ausgewählte Themen der Nichtlinearen und der Dynamischen Optimierung sowie der Simulation vorgestellt. Die Vorlesungsinhalte werden in Übungen und Fallstudien vertieft; dabei wird auch Microsoft Excel zur Lösung von Optimierungsproblemen sowie zur Simulation eingesetzt.

Operations Management (français) - Prof. Marino Widmer - Spring semester

Facteurs prioritaires de concurrence. Planification des processus et des produits. Aménagement de systèmes de production. Planification de la capacité à long terme. Gestion de la qualité. Prévision de la demande. Planification de la production (MRP). Gestion de stocks. Juste-à-temps et production au plus juste. Amélioration continue. Ordonnancement. Organisation de la chaîne logistique.


Operations Management (deutsch) -  Prof. Bernard Ries - Spring semester

Die Vorlesung befasst sich mit den strategischen und operativen Aufgaben des Operations Management. Es werden unter anderem folgende Themen behandelt: Einführung in das Operations Management; Prozessanalyse; Produktionsprozesse; Layoutplanung; Elemente der Warteschlangentheorie; Kapazitätsmanagement; Standortplanung; Nachfrageprognose; Projektmanagement; Bestandsmanagement; Ablaufplanung; Materialbedarfsplanung.
 

 

Master courses

Supply Chain Management & Logistics - Prof. Marino Widmer - Fall semester

This course considers the various aspects of the supply chain management (SCM), which lets an organization get the right goods and services to the place they are needed at the right time, in the proper quantity and at an acceptable cost. Efficiently managing this process involves overseeing relationships with suppliers and customers, controlling inventory, forecasting demand and getting constant feedback on what is happening at every link in the chain.  The main part of the course is about solution methods for supplier selection, warehouse location, demand forecasting, master planning, purchasing planning, operations scheduling, and vehicle routing. The course will contain an Operations Research primer (formulation of linear, nonlinear and integer programs; solution with Excel Solver-Add-In).


Graph Theory and Applications - Prof. Bernard Ries - Fall semester

In this course, we first introduce some basic concepts and notions of graph theory. We then present a series of graph theoretical problems (vertex coloring, edge coloring, maximum matching, …) which have real world applications (in sports scheduling, timetabling, transmission problems, … ) and focus on how these problems may be solved. The students will also learn how to model other real world problems using the graph theoretical notions introduced. With this course, the students will get familiar with the basic notions and fundamental problems in graph theory. They will learn how to use these theoretical problems to model real world problems as well as how to solve them.


Best Practice in Mathematical Modelling - PD Dr. Tony Hürlimann - Fall semester

This lecture provides an introduction into the process of formulating with mathematical models decision problems from various contexts, making them accessible to solving by powerful “solvers” (software implementation of generic optimization algorithms) available nowadays. While it has been said that modeling is an “art”, theoretical knowledge as well as some guidelines are needed to devise correct and efficient models. The lecture relies strongly on examples and “learning by doing”. Starting from various practical examples, we go through the process of abstraction and stepwise translation of a real-world decision problem to its formal representation by a mathematical model. We make use of the modeling language LPL and commercial solvers (Xpress, Cplex, Gurobi) and free solvers (glpk, lp_solve) to implement the mathematical models and solve them on the computer. During the course, each student receives a “case” project involving a practical decision problem, which she or he will model and solve, and present at the end of the course.


Advanced Topics in Decision Support - Prof. Bernard Ries - Spring semester

In this course, we start with a presentation of the basic notions in decision theory. We focus on several existing decision criteria and analyse their weaknesses and strengths. We also consider decision criteria under probabilistic uncertainty. We then present an introduction to utility theory, explain how to use utility functions and also how to construct such functions using loteries. Finally, we give a short introduction to multi-criteria decision theory and present some existing methods. All topics will be illustrated by examples taken from economics, management science and operations research.


Quantitative Models in Revenue Management - PD Dr. Tony Hürlimann - Spring semester

Pricing and revenue optimization is a quantitative approach for managing and updating pricing decisions in a consistent and effective fashion. This approach has proven particularly successful in the airline industry, with car rentals, hotel room bookings, etc., and is fostered by the development of e-commerce. This course – as part of the course cycle “Selected Topics in Decision Support” – introduces basics on pricing (finding optimal prices, the “right” price differentiation, etc.) and Revenue Management. It addresses capacity allocation of a single resource to multiple customer classes, network management (multiple resources), overbooking (allowing for no-shows and cancellations), and markdown management (reducing prices to clear inventory). Textbook (mandatory): Phillips R.L., Pricing and Revenue Optimization, Stanford University Press, 2005.


Transportation Logistics: Quantitative Models and Methods - PD Dr. Tony Hürlimann - Spring semester

This lecture provides an introductory overview of quantitative models in transportation and logistics. In all lectures, we start with a practical, real-life project that has been conceptualized and implemented for an existing company by the authors in the past. We go through the process of modelling and implementation in order to make the difficulties, pitfalls and challenges of real decision problems visible and apparent.
We make use of the rich tools and methods as well as models from the Operations Reaseach community to approach the practical problems with a theoretical background. We especially will use the modeling language LPL, spreadsheet modeling, programming and commercial Solvers packages to implement the mathematical models and solve them on the computer.