A general solution framework for component commonality problems

Component commonality, the use of the same version of a component across multiple products, is increasingly considered as a promising way to offer high external variety while retaining low internal variety in operations. However, increasing commonality has both positive and negative cost effects, so that optimization approaches are required to identify an optimal commonality level. As a more or less of components influences nearly every process step along the supply chain, it is not astounding that a multitude of diverging commonality problems is investigated in literature, each of which developing a specific algorithm designed for the respective commonality problem considered. The paper on hand aims at a general framework, flexible and effcient enough to be applied to a wide range of commonality problems. Such a procedure basing on a two-stage graph approach is presented and tested. Finally, flexibility of the procedure is shown by customizing the framework to account for different types of commonality problems.Product variety, Component commonality, Optimization, Graph approach

The Car Resequencing Problem with Pull-Off Tables

The car sequencing problem determines sequences of different car models launched down a mixed-model assembly line. To avoid work overloads of workforce, car sequencing restricts the maximum occurrence of labor-intensive options, e.g., a sunroof, by applying sequencing rules. We consider this problem in a resequencing context, where a given number of buffers (denoted as pull-off tables) is available for rearranging a stirred sequence. The problem is formalized and suited solution procedures are developed. A lower bound and a dominance rule are introduced which both reduce the running time of our graph approach. Finally, a real-world resequencing setting is investigated.mixed-model assembly line, car sequencing, resequencing

Global imbalances after the financial crisis.

Finanzmarktkrise; Wirtschaftskrise; Leistungsbilanz; Zahlungsbilanzungleichgewicht; Welt;

Umschlagbahnhöfe aus entscheidungsorientierter Sicht

Trotz intensiver Fördermaßnahmen für die Bahn durch den Bund und die EU verlagert sich das Transportaufkommen immer weiter in Richtung der Straße. Nachteile der Bahn bestehen etwa in einer geringeren Durchschnittsgeschwindigkeit und Zuverlässigkeit sowie einer geringen Flexibilität. Durch die effiziente Planung des Containerumschlags in Umschlagbahnhöfen können die Nachteile der Bahn jedoch abgemildert werden. Dieser Beitrag beschreibt neben dem grundlegenden Aufbau von Umschlagbahnhöfen die wichtigsten strategischen, taktischen und operativen Planungsprobleme zur Ermöglichung eines effizienten Containerumschlags.

Design und Betrieb von Cross Docks

Die hohen Anforderungen an heutige Wertschöpfungsnetzwerke in Bezug auf Flexibilität und Lieferbereitschaft stellen die Distribution vor die Aufgabe, Güter immer häufiger und in immer kleineren Mengen ausliefern zu müssen. Ein Ansatz, diesen Forderungen auf möglichst wirtschaftliche Art und Weise gerecht zu werden, besteht darin, bestehende Distributionsnetze um sogenannte Cross Docks zu erweitern. In solchen lagerlosen Umschlagzentren können dann kleine Warensendungen mit ähnlicher Destination zu vollständig ausgelasteten Lkw-Transporten konsolidiert werden, um sogenannte "economies in transportation" realisieren zu können. Neben den strategischen Überlegungen für und wider die Einführung von Cross Docks stehen in diesem Aufsatz insbesondere die Planungsprobleme im Mittelpunkt, die es im Rahmen der Errichtung und der täglichen Prozessabläufe in einem Cross Docking Terminal zu lösen gilt.

Robotized sorting systems: Large-scale scheduling under real-time conditions with limited lookahead

A major drawback of most automated warehousing solutions is that fixedly installed hardware makes them inflexible and hardly scalable. In the recent years, numerous robotized warehousing solutions have been innovated, which are more adaptable to varying capacity situations. In this paper, we consider robotized sorting systems where autonomous mobile robots load individual pieces of stock keeping units (SKUs) at a loading station, drive to the collection points temporarily associated with the orders demanding the pieces, and autonomously release them, e.g., by tilting a tray mounted on top of each robot. In these systems, a huge number of products approach the loading station with an interarrival time of very few seconds, so that we face a very challenging scheduling environment in which the following operational decisions must be taken in real time: First, since pieces of the same SKU are interchangeable among orders with a demand for this specific SKU, we have to assign pieces to suitable orders. Furthermore, each order has to be temporarily assigned to a collection point. Finally, we have to match robots and transport jobs, where pieces have to be delivered between loading station and selected collection points. These interdependent decisions become even more involved, since we (typically) do not posses complete knowledge on the arrival sequence but have merely a restricted lookahead of the next approaching products. In this paper, we show that even in such a fierce environment sophisticated optimization, based on a novel two-step multiple-scenario approach applied under real-time conditions, can be a serviceable tool to significantly improve the sortation throughput