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Item type:Publication, Access status: with files , Optimierung von Containertransporten im Hafenhinterland per LKW unter Berücksichtigung von Kooperationsmöglichkeiten(2024); The growth in container transportation worldwide in the past is a major challenge for players in the maritime supply chain regarding empty container logistics. The highest proportion of costs in the maritime supply chain arises from transportation in the port hinterland. Truck carriers are exposed to intense competition. Lack of economies of scale, low margins and service interchangeability require new solutions to strengthen their economic position. Here, in the scientific community the concept of horizontal collaboration is discussed, in which competitors exchange customer orders in a profit-maximizing manner. The aim of horizontal collaboration is not only to increase efficiency and profit for all parties involved, but also to establish it in a fair and stable manner in the long run. An interview study among truck carriers in Hamburg shows that the perception of the market is decisive for the willingness to collaborate. Those carriers who are proactive towards collaboration, prefer to share their customer orders only with selected trustworthy competitors. Furthermore, the academic literature supports the need for monetary and non-monetary benefits of collaboration to be fairly distributed among participants. Based on a literature review and an interview study, a mathematical model is developed and evaluated using two real-world case studies from the Hamburg port hinterland. This model makes a significant contribution to research, as it is the first to consider the aspects of trust groups, compensation payments and fairness mechanisms simultaneously. The application of the model shows that the profit rises with the size of the trust group. This is already the case for two collaborating carriers that form a trust group. It must be considered that own customer orders should be made available for sharing with the trust group. An evaluation regarding fuel consumption shows that avoiding empty container trips and empty trips also reduces CO2 emissions. The results also show that week-based fairness mechanisms achieve a higher profit increase compared to day-based fairness mechanisms. As a fundamental result it should be emphasized that a simultaneous application of profit- and customer order-based fairness mechanisms meets the aim of achieving a fair and long-term stable collaboration.Publicationtype: Doctoral Thesis69 178 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Optimierung geschlossener Wertschöpfungskreisläufe bei beschränkten Kapazitäten(2021-04-11); Nowadays, manufacturing companies are faced with the trade-off between cost minimization through mass production of standardized products and the production of individualized products at high costs. Flexible mass production with modularly designed products, component commonality and order-related production should be the solution to this dilemma. In addition, manufacturing companies are encouraged by social and legal requirements, but also for economic reasons, to take back their used products and remanufacture them. Products with a modular design are suitable for remanufacturing. In this work, a closed-loop supply chain with remanufacturing is examined: Products are returned by customers after use and can be processed in such a way that the components they contain are as good as new and used instead of externally procured components for the order-related manufacture of as-new modular products. Subsequently, a mathematical model for planning this closed-loop supply chain is developed. First, supply chains with reverse product flows are systematically analyzed in order to work out the special planning requirements and thus specifications for the mathematical modeling of the decision problem examined in this work. Quantitative methods for decision support are presented. However, these methods are not suitable for the decision problem of this work because they neglect special planning requirements in the modeling. The facility location problem is one such method; this model and the planning of supply chains using this model are discussed critically. A facility location problem for planning a closed-loop supply chain from the literature is corrected and solved for an example from the copier industry. The solutions show which problems arise from the inadequate mathematical mapping. Building on this knowledge the facility location problem will be expanded step by step. This procedure shows which new findings and improvements can be achieved through the further developed modeling of the decision problem. First of all, the facility location problem is expanded to include production planning with remanufacturing. The solutions for the example from the copier industry show that the mutual dependencies between location, transport and production planning in the supply chain are recorded. In addition, supplier locations and quantities are now considered in the planning. Then the modeling approach is expanded to include (volume) capacity planning and divided into a multi-period planning horizon. Now, the capacity is optimally determined together with the locations as well as the transport, procurement and processing quantities. The solutions prove that now high overcapacities are prevented and the relationship between transport and storage quantities is mapped with site capacities. Furthermore, the influence of product life cycles, customer usage duration of products and product design can now be examined. It can also be observed that the redistribution of production input is optimal under certain conditions. Since production with remanufacturing is labor-intensive, workforce planning must also be included in the modeling. This means that wage costs, processing times and the working hours available at the location are taken into account in the optimization. This planning is further improved by a differentiated modeling of the decision times. This results in a mathematical model that plans the location, capacity, transport, production and workforce of the closed-loop supply chain combined with their respective medium and long-term decision points. In this way, the influence of seasonally fluctuating demand on the supply chain, in particular on capacities, can be examined. With this detailed modeling, the capacity requirement can be determined more precisely and the recording of costs compared to the facility location problem is improved. Consequently, a detailed mathematical mapping of the decision problem is required so that recommendations for economically reasonable measures result.Publicationtype: Doctoral Thesis973 1527