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Optimizing Transport Logistics Processes with Multiagent Planning and Control
Optimizing Transport Logistics Processes with Multiagent Planning and Control
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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…
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 279
  • ISBN-10: 365814002X
  • ISBN-13: 9783658140021
  • Formatas: 14.8 x 21 x 1.6 cm, minkšti viršeliai
  • Kalba: Anglų

Optimizing Transport Logistics Processes with Multiagent Planning and Control (el. knyga) (skaityta knyga) | knygos.lt

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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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  • Autorius: Max Gath
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 279
  • ISBN-10: 365814002X
  • ISBN-13: 9783658140021
  • Formatas: 14.8 x 21 x 1.6 cm, minkšti viršeliai
  • Kalba: Anglų

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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