Advanced mathematical modeling and optimization

  • Enseignement

    Détails

    Faculté Faculté des sciences et de médecine
    Domaine Informatique
    Code UE-SIN.08611
    Langues Anglais
    Type d'enseignement Cours
    Cursus Master
    Semestre(s) SP-2020

    Horaires et salles

    Horaire résumé Jeudi 13:15 - 16:00, Hebdomadaire, PER 21, salle C130
    Struct. des horaires 3h par semaine durant 14 semaines
    Heures de contact 42

    Enseignement

    Responsables
    Enseignants
    Description

    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.

    Objectifs de formation

    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.

    Conditions d'accès

    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).

    Commentaire

    MSc-CS BENEFRI - (Code Ue: 53073 / Track: T5) The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/.

    Softskills
    Non
    Hors domaine
    Non
    BeNeFri
    Oui
    Mobilité
    Oui
    UniPop
    Non

    Documents

    Bibliographie

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

  • Dates et salles
    Date Heure Type d'enseignement Lieu
    20.02.2020 13:15 - 16:00 Cours PER 21, salle C130
    27.02.2020 13:15 - 16:00 Cours PER 21, salle C130
    05.03.2020 13:15 - 16:00 Cours PER 21, salle C130
    12.03.2020 13:15 - 16:00 Cours PER 21, salle C130
    19.03.2020 13:15 - 16:00 Cours PER 21, salle C130
    26.03.2020 13:15 - 16:00 Cours PER 21, salle C130
    02.04.2020 13:15 - 16:00 Cours PER 21, salle C130
    09.04.2020 13:15 - 16:00 Cours PER 21, salle C130
    23.04.2020 13:15 - 16:00 Cours PER 21, salle C130
    30.04.2020 13:15 - 16:00 Cours PER 21, salle C130
    07.05.2020 13:15 - 16:00 Cours PER 21, salle C130
    14.05.2020 13:15 - 16:00 Cours PER 21, salle C130
    28.05.2020 13:15 - 16:00 Cours PER 21, salle C130
  • Modalités d'évaluation

    Examen écrit

    Mode d'évaluation Par note
  • Affiliation
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