Advanced mathematical modeling and optimization

  • Unterricht

    Details

    Fakultät Math.-Nat. und Med. Fakultät
    Bereich Informatik
    Code UE-SIN.08611
    Sprachen Englisch
    Art der Unterrichtseinheit Vorlesung
    Kursus Master
    Semester SP-2020

    Zeitplan und Räume

    Vorlesungszeiten Donnerstag 13:15 - 16:00, Wöchentlich (Frühlingssemester)
    Strukturpläne 3h par semaine durant 14 semaines
    Kontaktstunden 42

    Unterricht

    Verantwortliche
    • Ries Bernard
    Dozenten-innen
    • Bürgy Reinhard
    Beschreibung

    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.

    Lernziele

    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.

    Zugangsbedingungen

    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).

    Bemerkungen

    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/.

    Soft Skills Nein
    ausserhalb des Bereichs Nein
    BeNeFri Ja
    Mobilität Ja
    UniPop Nein

    Dokument

    Bibliographie

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

  • Einzeltermine und Räume
    Datum Zeit Art der Unterrichtseinheit Ort
    20.02.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    27.02.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    05.03.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    12.03.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    19.03.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    26.03.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    02.04.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    09.04.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    23.04.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    30.04.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    07.05.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    14.05.2020 13:15 - 16:00 Kurs PER 21, Raum C130
    28.05.2020 13:15 - 16:00 Kurs PER 21, Raum C130
  • Leistungskontrolle

    Schriftliche Prüfung

    Bewertungsmodus Nach Note
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