Northwestern University Transportation Center (NUTC) is a leading interdisciplinary education and research institution serving industry, government, and the public. NUTC was founded in 1954 to make substantive and enduring contributions to the movement of materials, people, energy, and information. In so doing, NUTC aims to influence national and international transportation policy, management, operations, and technological developments.
Produced and maintained by the Transportation Research Board, TRID is the world's largest and most comprehensive bibliographic resource on transportation research information, covering all modes of transportation.
This contributed volume brings together research papers presented at the 4th International Conference on Dynamics in Logistics, held in Bremen, Germany in February 2014. The conference focused on the identification, analysis and description of the dynamics of logistics processes and networks. Topics covered range from the modeling and planning of processes, to innovative methods like autonomous control and knowledge management, to the latest technologies provided by radio frequency identification, mobile communication, and networking. The growing dynamic poses wholly new challenges: logistics processes and networks must be(come) able to rapidly and flexibly adapt to constantly changing conditions. The book primarily addresses the needs of researchers and practitioners from the field of logistics, but will also be beneficial for graduate students.
Max Gath presents a multiagent system for the optimization of transport logistics in highly complex and dynamic domains. The described solution dynamically optimizes processes and provides a high flexibility, scalability, robustness, and adaptability to individual customer demands. The experimental evaluation points out the effectiveness and efficiency by using the example of commonly applied benchmarks as well as two case studies in groupage traffic and in courier, express, and parcel services with same-day deliveries. Both case studies were performed with leading transport companies in Germany. The results demonstrate that the multiagent-based solution satisfies domain-specific requirements and exploits high optimization potential in real-world processes.
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