Advanced mathematical modeling and optimization

  • Teaching

    Details

    Faculty Faculty of Science and Medicine
    Domain Computer Science
    Code UE-SIN.08611
    Languages English
    Type of lesson Lecture
    Level Master
    Semester SA-2022

    Schedules and rooms

    Summary schedule Tuesday 14:15 - 17:00, Hebdomadaire (Autumn semester)
    Struct. of the schedule 3h par semaine durant 14 semaines
    Contact's hours 42

    Teaching

    Responsibles
    • Ries Bernard
    Teachers
    • Pacheco Paneque Meritxell
    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.

    Training objectives

    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.

    Condition of access

    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).

    Comments

    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/.

    Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/

    Softskills No
    Off field No
    BeNeFri Yes
    Mobility Yes
    UniPop No

    Documents

    Bibliography

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

  • Dates and rooms
    Date Hour Type of lesson Place
    20.09.2022 14:15 - 17:00 Cours PER 21, Room C130
    27.09.2022 14:15 - 17:00 Cours PER 21, Room C130
    04.10.2022 14:15 - 17:00 Cours PER 21, Room C130
    11.10.2022 14:15 - 17:00 Cours PER 21, Room C130
    18.10.2022 14:15 - 17:00 Cours PER 21, Room C130
    25.10.2022 14:15 - 17:00 Cours PER 21, Room C130
    08.11.2022 14:15 - 17:00 Cours PER 21, Room C130
    22.11.2022 14:15 - 17:00 Cours PER 21, Room C130
    29.11.2022 14:15 - 17:00 Cours PER 21, Room C130
    06.12.2022 14:15 - 17:00 Cours PER 21, Room C130
    13.12.2022 14:15 - 17:00 Cours PER 21, Room C130
    20.12.2022 14:15 - 17:00 Cours PER 21, Room C130
  • Assessments methods

    Written exam

    Assessments methods By rating
  • Assignment
    Valid for the following curricula:
    Additional Courses in Sciences
    Version: ens_compl_sciences
    Paquet indépendant des branches > Specialized courses in Computer Science (Master level)

    Additional programme requirements for PhD studies [PRE-DOC]
    Version: 2020_1/v_01
    Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Computer Science (Master level)

    Computer Science [3e cycle]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Computer Science (Master level)

    Computer Science [POST-DOC]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Computer Science (Master level)

    MSc in Computer science (BeNeFri)
    Version: 2023_1/V_01
    MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T5 : Information Systems and Decision Support

    Ma - Business Communication : Business Informatics - 90 ECTS
    Version: 2020/SA_V02
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Wirtschaftsinformatik > DADS: Data Analytics & Decision Support

    Ma - Business Informatics - 90 ECTS
    Version: 2020/SA-v01
    Classes - min. 45 ECTS > Modules IT Management - min. 22 ECTS > DADS: Data Analytics & Decision Support
    Classes - min. 45 ECTS > Module IT and IT Management > DADS: Data Analytics & Decision Support

    Ma - Management - 90 ECTS [MA]
    Version: 2017/SA_v01
    Courses: min. 63 ECTS > 3 modules with min 12 ECTS each > BINF: Business Informatics

    MiMa - Business Informatics - 30 ECTS
    Version: 2020/SA_V01
    Cours > Module Wirtschaftsinformatik > DADS: Data Analytics & Decision Support

    MiMa - Data Analytics - 30 ECTS
    Version: 2020/SA-v01
    À choix 9 crédits ECTS > DADS: Data Analytics & Decision Support