The problems treated in this book are very simple in nature: how to route n vehicles in real time in a fast varying environment to pickup and deliver m passengers when both n and m are large? These problems are very relevant to future transportation options involving large scale real-time routing of shared-ride fleet transit vehicles. But, even if the nature of these problems looks so simple, solving them is not so straight forward, specially finding fast and reliable solutions. Traditionally, dynamic routing solutions were found as static approximations for smaller-scale problems or using local heuristics for the larger-scale ones. Generally heuristics used for these types of problems do not consider global optimality. This work develops a hierarchical methodology to solve these types of problems in three stages seeking global optimality. The book first introduces the problems treated, secondly presents the main characteristics of the proposed methodology, followed by insights on each of the proposed stages. Then a general framework to use the proposed methodology for any vehicle routing problem is presented. Finally, a real application is presented. The work is addressed to professionals and researchers working on vehicle routing and network optimization issues.

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