Doktorarbeit: Tourenplanung von Speditionsunternehmen im Teilladungsverkehr mit Kundenzeitfenstern und heterogenem Fuhrpark

Tourenplanung von Speditionsunternehmen im Teilladungsverkehr mit Kundenzeitfenstern und heterogenem Fuhrpark

Modelle und Lösungsverfahren sowie Kooperationsmechanismen für kleine und mittelständische Speditionsunternehmen

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Logistik-Management in Forschung und Praxis, volume 70

Hamburg , 414 pages

ISBN 978-3-339-13084-6 (print) |ISBN 978-3-339-13085-3 (eBook)

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Due to the constantly increasing price pressure in the largely medium-sized transport industry, the number of freight forwarding companies has been declining in recent years, despite rising transport volumes. Particularly for small and medium-sized forwarding companies in the Less-Than-Truckload market, it is essential to develop solution strategies in order to stay in the market and to cope with large competitors.

One approach to solving this problem is the continuous optimization of vehicle routing with the target to save costs and to make the best possible use of the available transport capacities. In order to find a solution that is consistent with practice, it is necessary to include restrictions relevant in practice in the modelling of the problem. In the present research work, a vehicle routing problem of the Less-Than- Truckload sector is examined, for which different model formulations are analyzed and then on basis of the models Genetic Algorithms for the heuristic solution of the problem are developed. Four variants of the Genetic Algorithms are evaluated with respect to the best known solutions on large datasets. Moreover, a parameter tuning approach is presented to improve the solution quality of the Genetic Algorithms by choosing the best possible parameter combination, which controls the selection of the implemented operators.

In order to increase profits beyond optimized vehicle routing, horizontal cooperation is another solution strategy for small and medium-sized freight forwarding companies. In cooperations, profits can be increased by exchanging transportation requests, and a decentralized auction-based exchange mechanism has proven to be a suitable approach for this purpose. Such a mechanism is investigated in this research work with respect to various aspects. In particular, the stochastic Bundle Selection Problem, in which the auctioneer determines which request bundles are offered in the auction, is analyzed in detail. A scenario-based approach with two preselection strategies is developed. The methods are evaluated on four cooperation networks of different structure.

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