Approximate Dynamic Programming for Dynamic Vehicle Routing

✍ Scribed by Marlin Wolf Ulmer (auth.)

• Publisher: Springer International Publishing
• Year: 2017
• Tongue: English
• Leaves: 209
• Series: Operations Research/Computer Science Interfaces Series 61
• Edition: 1
• Category: Library

✦ Synopsis

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 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.

✦ Table of Contents

Front Matter....Pages i-xxv
Introduction....Pages 1-11
Front Matter....Pages 13-13
Rich Vehicle Routing: Environment....Pages 15-24
Rich Vehicle Routing: Applications....Pages 25-39
Modeling....Pages 41-61
Anticipation....Pages 63-69
Anticipatory Solution Approaches....Pages 71-102
Literature Classification....Pages 103-113
Front Matter....Pages 115-115
Motivation....Pages 117-122
SDVRP with Stochastic Requests....Pages 123-129
Solution Algorithms....Pages 131-146
Computational Evaluation....Pages 147-176
Conclusion and Outlook....Pages 177-181
Back Matter....Pages 183-197

✦ Subjects

Operation Research/Decision Theory;Operations Research, Management Science