Dr.-Ing. Matthias Stickel
- Alumnus
- Department of Logistics Systems
Karlsruher Institut für Technologie
Institut für Fördertechnik und Logistiksysteme
Geb. 50.38 Gotthard-Franz-Str. 8
76131 Karlsruhe
| Title | Image | Source | Short Description |
|---|---|---|---|
| Vehicle routing with regard to traffic prognosis and congestion probabilities | Advanced OR and AI Methods in Transportation, Hrsg.: Andzej Jaskiewics, Mariusz Kaczmarek, Jacek Zak, Marek, Kubiak, Publishin House of Poznan University of Technology, 2005, S.780-786 | This paper presents a new instance of the Vehicle Routing Problem with Time Windows (VRPTW) with regard to traffic forecasting and traffic congestion probabilities (VRPTWTP). Traffic prognosis is integrated by calculating time-dependent journey times, which rely on both the prognosis data for the anticipated traffic demand of the roadsection considered at a certain time and the probability of the occurrence of a traffic congestion. While computing tractability of the Mixed-Integer-Program increases, significant improvements regarding delivery accuracy and vehicle utilization can be obtained. This research was achieved within the project OVID, launched by the German Ministry of Research and Education. |
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| An optimal control policy for for crossdocking terminals | Selected Papers of the 2005 International Conference on Operations Research, Bremen, 2005: Gesellschaft für Operations Research (GOR), Springer, Berlin. Accepted for publication. | Crossdocking terminals are transhipment facilities without stock, for the rapid consolidation and shipment of products. The difference to traditional distribution centers is the complete elimination of all storage functions. In consequence of this elimination the incoming and outgoing shipments have to be exactly coordinated to achieve a transshipment operation at minimum cost. This paper describes a mixed-integer model for a centralized optimal control policy for crossdocking facilities, which takes into account the shipments of goods to the crossdocking terminal, the transfers inside the terminal as well as the shipments to the customers. A Branch-and-Bound algorithm has been applied to obtain an exact solution for the optimization model which is tested on different data sets. The results show that an exact solution can be obtained for small instances. Finally, the results for a decomposed model are presented. The decomposition yields faster results for larger instances and therefore is more applicable in practice. | |
| A web-based support tool to coordinate logistic activities in dense populated areas using auctions | Urban Transport XI, Editors. C.A. Brebbia and L.C. Wadhwa, WIT Press, 2005, S.601-607 | In the context of research project MOSCA, promoted by the European Union, a prototype of a web-based support tool (web-portal) was developed. It's purpose was to improve communication and coordination between participants of the traffic system. These participants were divided into two segments: the supply-side and the demand-side. The supply-side consists of cities and municipalities which "supply" the traffic infrastructure. On the other hand, the senders and receivers of goods (companies, stores) use ("demand") this traffic infrastructure. The starting point is the rising extent of utilization of the traffic system in urban areas, which today already reaches its capacity limits. In order to work against this, the city of Lugano in Switzerland, examined whether it is meaningful to limit the entry of trucks into the city. Only vehicles that can show proof of an existing parking bay will be granted admission to the city center. Thereby the possibility of dynamic pricing of parking areas and the assignment of parking bays by means of auctions were investigated. The suggested web-portal represents a technical possibility to implement such an access restriction. By publishing information of open capacities, all participants are enabled to realize more efficient plans of city-logistic activities in dense populated areas, since these information can be used in logistic planning algorithms. |