Pro-active Dynamic Vehicle Routing

Real-Time Control and Request-Forecasting Approaches to Improve Customer Service
2013
ISBN: 978-3-642-33471-9
Verlag: Springer

Buch, Englisch, 319 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 6801 g

Reihe: Contributions to Management Science

This book deals with transportation processes denoted as the Real-time Distribution of Perishable Goods (RDOPG). The book presents three contributions that are made to the field of transportation. First, a model considering the minimization of customer inconvenience is formulated. Second, a pro-active real-time control approach is proposed. Stochastic knowledge is generated from past request information by a new forecasting approach and is used in the pro-active approach to guide vehicles to request-likely areas before real requests arrive there. Various computational results are presented to show that in many cases the pro-active approach is able to achieve significantly improved results. Moreover, a measure for determining the structural quality of request data sets is also proposed. The third contribution of this book is a method that is presented for considering driver inconvenience aspects which arise from vehicle en-route diversion activities. Specifically, this method makes it possible to restrict the number of performed vehicle en-route diversion activities.

Zielgruppe

Research

Autoren/Hrsg.

Ferrucci, Francesco

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Transport- und Verkehrswirtschaft
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Kundenbeziehungsmanagement, Kundenpflege
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Vertrieb

Inhaltsverzeichnis

Introduction.- Introduction to Tour Planning: Vehicle Routing and Related Problems.- The Considered RDOPG Applications.- Review of the Literature Related to the Considered RDOPG Applications.- A New Deterministic Real-Time Control Approach for RDOPG Applications.- A New Forecasting Approach for Generating Stochastic Knowledge.- The Proposed Tabu Search Solution Method.- Computational Results.- Summary and Outlook on Future Work.- Appendix.- References.