13 search hits
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Das Optimierungslabor – ein Erfahrungsbericht
(2012)
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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.
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An exact column-generation approach for the lot-type design problem
(2012)
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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.
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A survey of the higher Stasheff-Tamari orders
(2012)
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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.
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The Stochastic Guaranteed Service Model with Recourse for Multi-Echelon Warehouse Management
(2012)
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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.
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Stability with uniform bounds for online dial-a-ride problems under reasonable load
(2011)
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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.
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Local Approximation of Discounted Markov Decision Problems by Mathematical Programming Methods
(2011)
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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.
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Exploiting combinatorial relaxations to solve a routing & scheduling problem in car body manufacturing
(2010)
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Jörg Rambau
Cornelius Schwarz
- Motivated by the laser sharing problem (LSP) in car body manufacturing, we define the new general routing and scheduling problem (RSP). In the RSP, multiple servers have to visit and process jobs; renewable resources are shared among them. The goal is to find a makespan-minimal scheduled dispatch. We present complexity results as well as a branch-and-bound algorithm for the RSP. This is the first algorithm that is able to solve the LSP for industrially relevant problem scales.
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How to avoid collisions in scheduling industrial robots?
(2010)
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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.
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On the benefits of using NP-hard problems in Branch & Bound
(2008)
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Jörg Rambau
Cornelius Schwarz
- We present a Brand-and-Bound (B&B) method using combinatorial bounds for solving makespan minimization problems with sequence dependent setup costs. As an application we present a laser source sharing problem arising in car manufacturing.
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The Top-Dog Index: A New Measurement for the Demand Consistency of the Size Distribution in Pre-Pack Orders for a Fashion Discounter with Many Small Branches
(2008)
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Sascha Kurz
Jörg Rambau
Jörg Schlüchtermann
Rainer Wolf
- We propose the new Top-Dog-Index, a measure for the branch-dependent historic deviation of the supply data of apparel sizes from the sales data of a fashion discounter. A common approach is to estimate demand for sizes directly from the sales data. This approach may yield information for the demand for sizes if aggregated over all branches and products. However, as we will show in a real-world business case, this direct approach is in general not capable to provide information about each branchs individual demand for sizes: the supply per branch is so small that either the number of sales is statistically too small for a good estimate (early measurement) or there will be too much unsatisfied demand neglected in the sales data (late measurement). Moreover, in our real-world data we could not verify any of the demand distribution assumptions suggested in the literature. Our approach cannot estimate the demand for sizes directly. It can, however, individually measure for each branch the scarcest and the amplest sizes, aggregated over all products. This measurement can iteratively be used to adapt the size distributions in the pre-pack orders for the future. A real-world blind study shows the potential of this distribution free heuristic optimization approach: The gross yield measured in percent of gross value was almost one percentage point higher in the test-group branches than in the control-group branches.
