QBWL Workshop

30th QBWL Workshop took place online (2021)

von QBWL Team am 15.03.2021, 13:10

This year’s QBWL workshop was hosted on 8 March 2021 by the Chair of Supply and Value Chain Management at TUM Campus Straubing. Due to the COVID-19 pandemic, the workshop was hosted in a virtual format.

116 participants from 18 universities joined the workshop which consisted of a large number of presentations and discussions. In three streams on “Last Mile Delivery, Routing & Logistics”, “ Revenue Management & Supply Planning”, and “Sequencing & Scheduling”, 20 researchers presented their current or future research projects. The presentations were complemented by vivid discussions.The agenda can be found below.

QBWL is a gathering of German research groups working on quantitative topics in business and economics. It was established about 3 decades ago and has continuously grown to a group of more than 25 chairs. The workshop is hosted once a year by one of the participating chairs, usually as a 3-day in-person workshop.

Next year’s workshop is planned for March 28-31, 2022 in Kloster Drübeck, hosted by Prof. Sven Müller from the University of Magdeburg.

 


30th QBWL Workshop online (2021)

von QBWL Team am 29.10.2020, 14:35


The 30. QBWL Workshop takes place March 8. - 9. 2021. The format will be online.

 

For further information, see the "Workshop" section.

Aus der Forschung

Robust Car Sequencing (M. Grunow)

von QBWL Team am 12.04.2021, 15:13

Das Team aus dem Operations and Supply Chain Management Department der TUM School of Management (Tu München) von Prof. Dr. Martin Grunow stellt im Artikel

Robust car sequencing for automotive assembly

einen innovativen robusten Sequencing Ansatz aus der Produktionsplanung für Automobilhersteller vor. Der Artikel erscheint im Juni 2021 im European Journal of Operational Research.

Abstract

Just-in-sequence material supply is the status quo in the automotive industry. In this process, the assembly sequence of vehicles is set several days prior to production, and communicated to the suppliers. The committed sequence is essential for efficient operations both at the original equipment manufacturer and its suppliers. In practice, however, sequence stability is insufficient. Short-term disruptions, such as quality problems and missing parts, put the sequence at risk. If a disruption occurs, the affected vehicle is removed from the sequence. The resulting gap is closed by bringing the succeeding vehicles forward. Such sequence alterations, however, cause workload changes and potentially work overloads at the assembly stations. As a remedial measure, additional sequence alterations are necessary, which further disturb material supply. Robustness against short-term sequence alterations is currently a key objective of automotive manufacturers.

In this paper, we propose a sequencing approach that includes the vehicles’ failure probabilities in order to generate robust sequences. Robust sequences are sequences that can be operated without modifications, even when vehicles fail. We develop a branch-and-bound algorithm that optimally solves small-sized instances. For large-sized instances, we design a sampling-based adaptive large neighborhood search heuristic. The superiority of our approach is validated in a simulation study using real-world data from a major European manufacturer. We find reductions in the expected work overloads of 72% and 80%, compared to the industry solution, and compared to an approach taken from literature which does not take failures into account.

Link

https://doi.org/10.1016/j.ejor.2020.10.004

Zitation

Andreas Hottenrott, Leon Waidner, Martin Grunow (2021)
Robust car sequencing for automotive assembly,
European Journal of Operational Research, Volume 291, Issue 3, 2021,Pages 983-994,
DOI: 10.1016/j.ejor.2020.10.004

Online veröffentlicht: Oktober 2020

 

Fixed interval scheduling (E. Pesch)

von QBWL Team am 12.04.2021, 15:14

Im April 2021 erscheint in der Zeitschrift Networks der Artikel

Fixed interval scheduling with thrid-party machines 

von Prof. Dr. Erwin Pesch und seinem Forscherteam.

Abstract

We study a problem of scheduling n jobs on machines of two types: in‐house machines and third‐party machines. Scheduling on in‐house machines incurs no additional costs, while using third‐party machines implies costs depending on their number and the time of usage. Each job has a fixed time interval for being processed which can be divided and allocated among several machines, as long as there is only one machine processing the job at any time. No machine can process more than one job at a time. Jobs can be rejected, and they are of different importance that is reflected in the weight of each job. The objective is to find a subset of the jobs and the number of third‐party machines for any period of time so that the accepted jobs can be feasibly scheduled, the total weight of the accepted jobs is maximized, and the total machine usage costs does not exceed a given upper bound. We also study a similar problem in which the objective is to maximize the total time at which at least one job is processed. Both problems are encountered in situations in which certain activities with given start and completion times have to be serviced by human operators. Examples are air traffic control and the monitoring safe vehicle unloading. Other examples are the employment of subcontractors in agriculture, construction or transportation. We will present NP‐hardness proofs, polynomial and pseudo‐polynomial optimal algorithms and an approximation algorithm for these problems and their special cases. These problems admit graph‐theoretical interpretations associated with finding independent sets and a proper vertex coloring in interval graphs.

Link 

https://doi.org/10.1002/net.21973

Zitation

Fridman, I, Kovalyov, MY, Pesch, E, Ryzhikov, A. (2021)
Fixed interval scheduling with third-party machines. Networks, 2021, 77: 361– 371, DOI: 10.1002/net.21973

Online veröffentlicht: August 2020

Best Paper Award 2021

von QBWL Team am 23.03.2021, 23:41

Am 16.03.2021 zeichnete der VHB ein Team aus den Reihen der QBWL Community mit dem Best Paper Award 2021 aus!

Prof. Dr. Sven Müller (Universität Magdeburg), Prof. Dr. Knut Haase, Dr. Matthes Koch (beide Universität Hamburg) und Mathias Kasper (TU Dresden) erhielten den Preis für ihren Artikel A Pilgrim Scheduling Approach to Increase Safety During the Hajj. Der Artikel beschreibt einen Simulations- und Optimierungsansatz, mit dem das Team die saudi-arabische Regierung bei der Planung von Massenbewegungen während der Pilgerfahrt nach Mekka unterstützt hat.

Der VHB ist mit über 2000 Mitgliedern die größte Vereinigung der deutschsprachigen Universitäts-Hochschullehrer. Der Best Paper Award wird jedes Jahr durch ein Auswahlgremium vergeben. Aktuell waren 11 Arbeiten nominiert.

Links:

VHB Meldung auf Twitter

VHB Best Paper Award

Link zum Artikel

Neuigkeiten auf der Webseite

von Matthes Koch am 15.03.2021, 22:09

Willkommen auf der Webseite des QBWL Workshops!

In den letzten Tagen wurde die Webseite etwas überarbeitet. Zusätzlich zu den aktuellen Informationen rund um den Workshop - in der linken Spalte - sollen hier zukünftig auch unregelmäßig Forschungsneuigkeiten aus der QBWL Community auftauchen. Gerne können Sie Neuigkeiten, etwa neue Veröffentlichungen, abgeschlossene Dissertationen u.ä. einsenden. Um Spam zu verhindern, müssen eingesendete Neuigkeiten noch vom QBWL Admin freigegeben werden.

Eine zweite Neuerung ist das Bilderalbum: Fotos der Workshops können hier eingestellt werden. Falls Sie noch Fotos vergangener Workshops einstellen wollen, dann schicken Sie diese gerne an info@qbwl.de .

Vorschläge, Ideen oder sonstige Unterstützung in der Weiterentwicklung der QBWL Webseite immer gerne an info@qbwl.de !