© 2017

Approximate Dynamic Programming for Dynamic Vehicle Routing

  • First monograph to provide a comprehensive overview of stochastic dynamic vehicle routing problems (SDVRPs)

  • Demonstrates the advantages of the approximate dynamic programming (ADP) compared to conventional heuristics

  • Accompanies the ADP methodology with illustrative examples from the field of SDVRPs


Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 61)

Table of contents

  1. Front Matter
    Pages i-xxv
  2. Marlin Wolf Ulmer
    Pages 1-11
  3. Dynamic Vehicle Routing

    1. Front Matter
      Pages 13-13
    2. Marlin Wolf Ulmer
      Pages 15-24
    3. Marlin Wolf Ulmer
      Pages 25-39
    4. Marlin Wolf Ulmer
      Pages 41-61
    5. Marlin Wolf Ulmer
      Pages 63-69
    6. Marlin Wolf Ulmer
      Pages 71-102
    7. Marlin Wolf Ulmer
      Pages 103-113
  4. Stochastic Customer Requests

    1. Front Matter
      Pages 115-115
    2. Marlin Wolf Ulmer
      Pages 117-122
    3. Marlin Wolf Ulmer
      Pages 123-129
    4. Marlin Wolf Ulmer
      Pages 131-146
    5. Marlin Wolf Ulmer
      Pages 147-176
    6. Marlin Wolf Ulmer
      Pages 177-181
  5. Back Matter
    Pages 183-197

About this book


This book provides a straightforward overview for every researcher interested in stochastic dynamic vehicle routing problems (SDVRPs). The book is written for both the applied researcher looking for suitable solution approaches for particular problems as well as for the theoretical researcher looking for effective and efficient methods of stochastic dynamic optimization and approximate dynamic programming (ADP). To this end, the book contains two parts. In the first part, the general methodology required for modeling and approaching SDVRPs is presented. It presents adapted and new, general anticipatory methods of ADP tailored to the needs of dynamic vehicle routing.  Since stochastic dynamic optimization is often complex and may not always be intuitive on first glance, the author accompanies the theoretical ADP-methodology with illustrative examples from the field of SDVRPs.

The second part of this book then depicts the application of the theory to a specific SDVRP. The process starts from the real-world application. The author describes a SDVRP with stochastic customer requests often addressed in the literature,  and then shows in detail how this problem can be modeled as a Markov decision process and presents several anticipatory solution approaches based on ADP. In an extensive computational study, he shows the advantages of the presented approaches compared to conventional heuristics. To allow deep insights in the functionality of ADP, he presents a comprehensive analysis of the ADP approaches.


Operations Research Vehicle Routing Stochastic Dynamic Optimization Dynamic Vehicle Routing SDVRPs SDO Rich Vehicle Routing

Authors and affiliations

  1. 1.Carl-Friedrich-Gauß-FakultätTechnische Universität BraunschweigBraunschweigGermany

About the authors

Marlin Ulmer is a Graduate in Mathematics and owns a Doctorate Degree in Economics. He is currently a Research Associate at the Carl-Friedrich Gauß Department of the Technische Universität Braunschweig in Germany. His main research field is Prescriptive Analytics in Transportation. His particular research interests are Vehicle Routing, Stochastic Optimization, and Approximate Dynamic Programming.

Bibliographic information

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