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Since 2019, Matheon's application-oriented mathematical research activities are being continued in the framework of the Cluster of Excellence MATH+
www.mathplus.de
The Matheon websites will not be updated anymore.

Julie Meißner

Staff of Project MI1

TU Berlin, Mathematik
Straße des 17. Juni 136
10623 Berlin
+49 (0) 30 314 22461
jmeiss@math.tu-berlin.de
Website


Research focus

Optimierung unter Unsicherheit,
Explorierung genauer Daten für verbesserte Worst-Case Garantien,
Approximationsalgorithmen

Projects as a member

  • MI1

    Design and operation of infrastructure networks under uncertainty

    Prof. Dr. Martin Skutella

    Project heads: Prof. Dr. Martin Skutella
    Project members: Julie Meißner
    Duration: -
    Status: completed
    Located at: Technische Universität Berlin

    Description

    Uncertainty in the input data is an omnipresent issue in most real world planning processes. Metropolitan infrastructure -its design, operation and maintenance- induces complex planning processes where data uncertainty lies, e. g. in processing durations, transit times, cost, market prices, customer demands, capacity, bandwidth, energy consumption, et cetera. Since decisions on the infrastructure are typically very cost-intensive and of long-term impact, there is an urgent need of best possible mathematical support in this decision making process.

    The quality of solutions for optimization problems (e. g. in infrastructure networks) with uncertain input data crucially depends on the amount of uncertainty. More information, or even knowing the exact data, allows for significantly improved solutions. It is impossible to fully abolish/avoid uncertainty. Nevertheless, it is sometimes possible to obtain exact data, but it may involve certain exploration cost in time, money, energy, bandwidth, etc.

    In telecommunication networks planning, for example, information on the existing infrastructure (copper lines, optical fiber etc.) or the transmission range might not be easily available. The challenging major task of this project is to develop a structural understanding and algorithmic methods on how to balance the cost for data exploration with the actual benefit for the quality of solution to the optimization problem under consideration.

    Project Webpage

    http://www.coga.tu-berlin.de/index.php?id=159901

Projects as a guest