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Author

  • Sascha Kurz (17)
  • Jörg Rambau (10)
  • Cornelius Schwarz (4)
  • Axel Kohnert (2)
  • Konrad Schade (2)
  • Miriam Kießling (2)
  • Tobias Kreisel (2)
  • Alfred Wassermann (1)
  • Andreas Tuchscherer (1)
  • Andrey Radoslavov Antonov (1)

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  • Preprint (26) (remove)

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  • Kombinatorik (9)
  • integral distances (6)
  • erschöpfende Suche (5)
  • exhaustive search (5)
  • ganzzahlige Abstände (5)
  • Durchmesser (4)
  • ganzzahlige Punktmengen (4)
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  • Diskrete Optimierung (3)
  • diameter (3)

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  • Mathematik (26)
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  • Wirtschaftswissenschaften (1)

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Show/Hide Abstract The Integrated Size and Price Optimization problem (2012)
Miriam Kießling Sascha Kurz Jörg Rambau
We present the Integrated Size and Price Optimization Problem (ISPO) for a fashion discounter with many branches. Based on a two-stage stochastic programming model with recourse, we develop an exact algorithm and a production-compliant heuristic that produces small optimality gaps. In a field study we show that a distribution of supply over branches and sizes based on ISPO solutions is significantly better than a one-stage optimization of the distribution ignoring the possibility of optimal pricing.
Show/Hide Abstract Das Optimierungslabor – ein Erfahrungsbericht (2012)
Miriam Kießling Tobias Kreisel Sascha Kurz Jörg Rambau Konrad Schade Cornelius Schwarz
Seit mehreren Jahren besuchen uns Schülerinnen und Schüler an der Universität zu Anlässen wie dem Tag der Mathematik, dem Girls’ Day, der MINT-Universität oder einfach auf Initiative ihrer Klassenleitungen. Sie möchten einen Einblick in die Welt der Mathematik über die Schulmathematik hinaus bekommen. Doch wie lässt sich die Brücke vom Schulstoff zu den Inhalten der Universitätsmathematik schlagen? Und: findet man einen Themenschwerpunkt, bei dem ein aktives Mitmachen trotz fehlender Vorkenntnisse in Anbetracht begrenzter Zeit möglich wird? In der diskreten Optimierung lassen sich Problem-Modellierung und Problem-Lösung sehr gut trennen. Selbst forschungsnahe Modelle der ganzzahligen linearen Optimierung (MILP-Modelle) basieren auf sehr elementaren Überlegungen, wie die Entscheidungsmöglichkeiten, Ziele und Restriktionen eines Alltagsproblems in Variablen, Bewertungsfunktionen, Gleichungen und Ungleichungen ausgedrückt werden können. Wie dann optimale Lösungen gefunden werden, erfordert zwar tiefergehende Mathematik, es gibt aber Software dafür, in der das Wissen aus Teilen des Mathematik-Studiums und der mathematischen Forschung kondensiert vorliegt. Unser Vermittlungsziel: Schülerinnen und Schüler wissen nach dem Besuch, dass man verschiedenste Probleme angreifen kann, indem man sie in die Sprache der Mathematik übersetzt, denn in Software gegossenes mathematisches Know-How kann dann diese Probleme lösen, ohne etwas über die Probleme selbst zu wissen. Unsere Idee für eine Maßnahme: Ein Optimierungslabor. Die Schülerinnen und Schüler isolieren in Teamarbeit die wesentlichen logischen Merkmale von Sudokulösen, Rucksackpacken, Routenplanung u.v.a.m. Dann übersetzen sie die Problemstellungen in die Sprache der Mathematik (hier: MILP-Modelle) und lassen sie (unterstützt durch unser Team) von Computerprogrammen lösen (MILP-Löser), die nichts anderes als diese Sprache verstehen. Schließlich übersetzen sie die mathematischen Lösungen wieder in die Sprache der Problemstellung. Erfahrungen mit der Modellierung auf Basis linearer Gleichungssysteme können dabei aus dem Schulunterricht eingebracht werden. In diesem Bericht wollen wir unsere Erfahrungen mit konkreten Details der Umsetzung schildern.
Show/Hide Abstract An exact column-generation approach for the lot-type design problem (2012)
Sascha Kurz Miriam Kießling Jörg Rambau
We consider a fashion discounter distributing its many branches with integral multiples from a set of available lot-types. For the problem of approximating the branch and size dependent demand using those lots we propose a tailored exact column generation approach assisted by fast algorithms for intrinsic subproblems, which turns out to be very efficient on our real-world instances.
Show/Hide Abstract A survey of the higher Stasheff-Tamari orders (2012)
Jörg Rambau Victor Reiner
The Tamari lattice, thought as a poset on the set of triangulations of a convex polygon with n vertices, generalizes to the higher Stasheff-Tamari orders on the set of triangulations of a cyclic d-dimensional polytope having n vertices. This survey discusses what is known about these orders, and what one would like to know about them.
Show/Hide Abstract The Stochastic Guaranteed Service Model with Recourse for Multi-Echelon Warehouse Management (2012)
Jörg Rambau Konrad Schade
The Guaranteed Service Model (GSM) computes optimal order-points in multi-echelon inventory control under the assumptions that delivery times can be guaranteed and the demand is bounded. Our new Stochastic Guaranteed Service Model (SGSM) with Recourse covers also scenarios that violate these assumptions. Simulation experiments on real-world data of a large German car manufacturer show that policies based on the SGSM dominate GSM-policies.
Show/Hide Abstract Stability with uniform bounds for online dial-a-ride problems under reasonable load (2011)
Sven O. Krumke Jörg Rambau
In continuously running logistic systems (like in-house pallet transportation systems), finite buffer capacities usually require controls achieving uniformly bounded waiting queues (strong stability). Standard stochastic traffic assumptions (arrival rates below service rates) can, in general, not guarantee these strong stability requirements, no matter which control. Therefore, the worst-case traffic notion of reasonable load was introduced, originally for the analysis of the Online-Dial-a-Ride Problem. A set of requests is reasonable if the requests that are presented in a sufficiently large time period can be served in a time period of at most the same length. The rationale behind this concept is that the occurrence of non-reasonable request sets renders the system overloaded, and capacity should be extended. For reasonable load, there are control policies that can guarantee uniformly bounded flow times, leading to strong stability in many cases. Control policies based on naive eoptimization, however, can in general achieve neither bounded flow times nor strong ability. In this chapter, we review the concept and examples for reasonable load. Moreover, we present new control policies achieving strong stability as well as new elementary examples of request sets where naive reoptimization fails.
Show/Hide Abstract Local Approximation of Discounted Markov Decision Problems by Mathematical Programming Methods (2011)
Stefan Heinz Jörg Rambau Andreas Tuchscherer
We develop a method to approximate the value vector of discounted Markov decision problems (MDP) with guaranteed error bounds. It is based on the linear programming characterization of the optimal expected cost. The new idea is to use column generation to dynamically generate only such states that are most relevant for the bounds by incorporating the reduced cost information. The number of states that is sufficient in general and necessary in the worst case to prove such bounds is independent of the cardinality of the state space. Still, in many instances, the column generation algorithm can prove bounds using much fewer states. In this paper, we explain the foundations of the method. Moreover, the method is used to improve the well-known nearest-neighbor policy for the elevator control problem.
Show/Hide Abstract A generalized job-shop problem with more than one resource demand per task (2011)
Joachim Schauer Cornelius Schwarz
We study a generalized job-shop problem called the Laser Sharing Problem with fixed tours (LSP-T) where the tasks may need more than one resource simultaneously. This fact will be used to model possible collisions between industrial robots. For three robots we will show that the special case where only one resource is used by more than one robot is already NP-hard. This also implies that one machine scheduling with chained min delay precedence constraints is NP-hard for at least three chains. On the positive side, we present a polynomial algorithm for the two robot case and a pseudo-polynomial algorithm together with an FPTAS for an arbitrary but constant number of robots. This gives a sharp boundary of the complexity status for a constant number of robots.
Show/Hide Abstract How to avoid collisions in scheduling industrial robots? (2010)
Jörg Rambau Cornelius Schwarz
In modern production facilities industrial robots play an important role. When two ore more of them are moving in the same area, care must be taken to avoid collisions between them. Due to expensive equipment costs our approach to handle this is very conservative: Each critical area is modeled as a shared resource where only one robot is allowed to use it at a time. We studied collision avoidance in the context of arc welding robots in car manufacture industry. Here another shared resource comes into place. When using laser welding technology every robot needs to be connected to a laser source supplying it with the necessary energy. Each laser source can be connected to up to six robots but serve only one at a time. An instance of the problem consists of a set of robots, a set of welding task, a number of laser sources, a distance table, collision information and a production cycle time. The goal is to design robot tours covering all task and schedule them resource conflict free such that the makespan does not exceed the cycle time. We propose a general model for integrated routing and scheduling including collision avoidance as well as a branch-and-bound algorithm for it. Computational results on data generated with the robot simulation software KuKa Sim Pro are also provided showing that our algorithm outperforms standard mixed-integer models for our application.
Show/Hide Abstract Bounds for the minimum oriented diameter (2008)
Sascha Kurz Martin Lätsch
We consider the problem of finding an orientation with minimum diameter of a connected bridgeless graph. Fomin et. al. discovered a relation between the minimum oriented diameter an the size of a minimal dominating set. We improve their upper bound.

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