Our group offers courses for bachelor and master students in information systems, computer science, management, and economics. Below you can find the courses related to decision support and operations research that are currently given (further information can be found on the webpage of the University). Hereafter, you also find some examples of  BA or MA theses in the field of Decision Support & Operations Research. Note that we currently have several industrial projects within which students can do a BA or MA thesis. If you are interested, please do not hesitate to contact us

Bachelor Courses

  • Algorithmik - Dr. Reinhard Bürgy - Fall semester

    In dieser Vorlesung werden zentrale Entwurfsmuster für Algorithmen, klassische algorithmische Probleme und Lösungsansätze, sowie elementare wie auch komplexere Datenstrukturen behandelt.

    Entwurfsmuster beschreiben generelle Vorgehensweisen für die Entwicklung von Algorithmen. Wir betrachten insbesondere Rekursions- und Induktionsverfahren, Divide-and-Conquer, Backtracking und dynamische Programmierung.


    Eine Menge von algorithmischen Problemen hat sich über die Jahre als Standardelemente der Informatik etabliert und elegante Datenstrukturen und Algorithmen wurden für diese entwickelt. Wir befassen uns insbesondere mit folgenden Problemen, Datenstrukturen und Algorithmen:

    • Sortieren: Mergesort und Quicksort
    • Suchen: Symboltabellen, binäre Suchbäume, balancierte Suchbäume, Hashtabellen
    • Graphen: spannende Bäume, kürzeste Wege, Minimale Flüsse
    • Strings (Zeichenketten): Stringsuche, Tries, reguläre Ausdrücke, Datenkompression


    Anwendungen aus der Praxis und der Wissenschaft veranschaulichen die Konzepte.


    Link zum Kurs

  • 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


    Les objectifs du cours sont:
    1) Comprendre et pouvoir décrire les modèles d’optimisation en aide à la décision. 
    2) Comprendre les concepts mathématiques de base pour les modèles d’optimisation. 
    3) Pouvoir utiliser la programmation linéaire pour modéliser des problèmes complexes ; savoir utiliser la méthode du simplexe, connaitre la dualité et l’analyse de sensibilité. 
    4) Connaitre les modèles d’optimisation linéaire en nombres entiers, leurs limites et les cas pouvant être résolus en temps polynomial; pouvoir modéliser des problèmes complexes à l’aide de la programmation mathématique linéaire en nombres entiers.


    Lien vers le cours.

  • Decision Support II (deutsch) - Prof. Norbert Trautmann (Universität Bern) - 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.


    Link zum Kurs.

  • Operations Management (deutsch) - Dr. Reinhard Bürgy - 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.


    Link zum Kurs.

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

    Planification des processus et des produits. Aménagement de systèmes de production. Planification de la capacité à long terme. 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.


    Lien vers le cours.

Master Courses

  • Quantitative pricing and revenue optimization - Dr. Reinhard Bürgy - Fall semester

    Pricing and revenue optimization, also called revenue management, is a quantitative approach to setting and updating pricing and product availability decisions in a consistent and effective fashion. This approach has proven particularly successful in the airline industry, where fares and ticket offerings dynamically change as a function of the number of free seats, forecast of future demand and specific request characteristics. 

    Fostered by the development of online business and big data technologies, the adoption of revenue management has not only changed the airline sector but disruptively transformed the transportation, hospitality and advertising industries. In fact, revenue management is becoming increasingly important in a broad range of sectors including finance, retail and manufacturing.

    Through a mix of lectures, case studies and guest speakers, we thoroughly discuss tactical decisions related to pricing and capacity allocation faced by companies that have some power to divide their customers into segments and to charge different prices to each segment. We first introduce the basics on pricing with and without a capacity (also called supply) constraint, then discuss price differentiation aspects and look at revenue optimization problems including customer segmentation. From these single resource problems, we move to the network case, in which multiple resources are used to provide a service. We also address overbooking aspects for dealing with no-shows and cancellations, and discuss markdown management for clearance of the inventory.

    We typically use (relatively simple) quantitative models to address the revenue optimization problems under study. We therefore assume that the students have some basic knowledge of mathematical modeling and optimization including how to mathematically describe an optimization problem, how to implement it in a spreadsheet, how to get a solution, and how to interpret it.


    Link to the course.

  • Graph Theory and Applications - Dr. David Schindl - 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.


    Link to the course.

  • 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. To reach these objectives, this course will be composed of the following parts:

    1. an introduction to the integrated production management (IPM) and an analysis of each module of the IPM
    2. supply chain management: strategic level
    3. supply chain management: operational level


    Lien vers le cours.

  • 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 particularly focus on decision criteria under probabilistic uncertainty and o how to handle additional information in a decision process. We then present an introduction to utility theory, explain how to use utility functions and also how to construct such functions using loteries.

    In a second part, we will concentrate on network optimization problems (max flow, min cost flow, etc...). Our focus will be on the modeling part but we will also see how to solve such problems efficiently.

    Finally, we give a short introduction to multi-criteria decision theory and present some existing methods (ELECTRE, AHP).

    All topics will be illustrated by examples taken from economics, management science and operations research.


    Link to the course.

  • Advanced mathematical modeling and optimization - Dr. Reinhard Bürgy - Spring semester

    This course considers modeling and optimization aspects of mixed-integer linear programming (or integer programming for short). This important subdomain of mathematical programming and extension of linear programming considers the problem of optimizing a linear function of many variables, some or all of them restricted to be integers, subject to linear constraints.

    Integer programming is a thriving area of optimization. It has countless applications in production planning and scheduling, logistics, layout planning and revenue management, to name just a few. Thanks to effective and reliable software, it is widely applied in industry to improve decision-making.

    In this course, we cover the theory and practice of integer programming. In the first part, we address mathematical modeling aspects. We discuss how integer variables can be used to model various practically relevant, complex decision problems. We then introduce some standard optimization problems and develop, analyze and compare different integer programming formulations for them. We also introduce powerful modeling and solving tools and test them on the optimization problems given in the course. In the second part, we address optimization aspects, in which we discuss the basic methodology applied to solve integer programs. In particular, we consider implicit enumeration techniques (branch and bound), polyhedral theory, cutting planes and primal heuristics. We also look at some advanced techniques, such as Danzig-Wolfe decomposition and column generation.



    With this course, the students gain the ability to formulate and solve practically relevant decision problems using integer programming, and they understand the basic methodology for solving integer programs and its implications with respect to modeling decisions.



    This course is designed for information systems, computer science and management student who have a good understanding of modeling and solving linear programs (as taught in the course Decision Support I).



    Conforti, Michele, Gérard Cornuéjols, and Giacomo Zambelli. Integer programming, Graduate Texts in Mathematics. Springer (2014).


    Link to the course.

Student Projects

General information

If you are interested in doing a BA or MA thesis in the field of Decision Support & Operations Research, do not hesitate to contact us.


Selected projects

End time Project Title Project type (study program) Student Supervisor
Ongoing A decomposition method for a path partitioning problem Bachelor thesis (Infomation Systems) Valentin Mulder Reinhard Bürgy
Ongoing Constructive and local search heuristics for the precedence-constrained class sequencing problem Bachelor thesis (Informatics) Boris Mottet Reinhard Bürgy
Ongoing A web-based waste collection game Bachelor thesis (Informatics) Mevlüt Tatli Reinhard Bürgy, Maurizio Rigamonti
Ongoing Combinatorial heuristics for a two-level waste collection problem Master thesis (Information Management) Alain Kolp Reinhard Bürgy
Ongoing Combinatorial algorithms for large-scale train scheduling on a complex rail network (industrial partner: SBB) Master thesis (Informatics) Fabio Degiacomi Reinhard Bürgy
Oct 2019 Scheduling a large Asian Soccer League Bachelor thesis (Informatics) Jonas Diesbach Reinhard Bürgy
Aug 2017 Analyse der Tourenplanung eines Online-Supermarktes Master thesis (Information Management) Vera Fischer Bernard Ries, Tony Hürlimann
Aug 2017 Utilisation de méthodes heuristiques dans le cadre de l'optimisation des tournées de livraison Master thesis (Management) Lenna Gerber Marino Widmer
Aug 2017 Ottimizzazione del reparto delle manutenzioni del "Relais Villa D'Amelia" in Piemonte, Italia Bachelor thesis (Management) Caroline Julmy Marino Widmer
Aug 2017 Ottimizzazione dei flussi di produzione - La casa farmaceutica IBSA Master thesis (Management) Ilaria Carlini Marino Widmer
Jun 2017 The Application of Multiple Criteria Decision Analysis Methods on Discrete Choice Problems Master thesis (Management) Mohammad Aldabbas Marino Widmer
Apr 2017 Projektplanung: Mobiles Container-restaurant Bachelor thesis (Management) Jonas Urwyler Bernard Ries
Nov 2016 Amélioration des systèmes de production - Des pratiques Lean aux concepts d'industrie 4.0 (Wifag - Polytype) Bachelor thesis (Management) Grégoire Bovet Marino Widmer
Aug 2016 Le potentiel de réduction des coûts de VR Group grâce à l'analyse Quick Scan Bachelor thesis (Management) Nicolas Donzallaz Marino Widmer
Aug 2016 Modélisation et optimisation des flux de masse de l'usine Cailler Master thesis (Management) Andrea Guidicelli Marino Widmer
Sep 2016 Système d'aide à la décision: Conception et développement d'un calculateur d'itinéraire optimal pour véhicules électriques Bachelor thesis (Information Systems) Loïc Voillat Bernard Ries