Approximate Dynamic Programming for Dynamic Vehicle Routing

by Marlin Wolf Ulmer

Overview

This book provides a straightforward overview for every researcher interested in shastic 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 shastic 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 shastic 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 shastic 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.

Product Details

ISBN-13:	9783319555102
Publisher:	Springer International Publishing
Publication date:	04/21/2017
Series:	Operations Research/Computer Science Interfaces Series , #61
Edition description:	1st ed. 2017
Pages:	197
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

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, Shastic Optimization, and Approximate Dynamic Programming.

Table of Contents

Introduction.- Part I: Dynamic Vehicle Routing.- Rich Vehicle Routing: Environment.- Rich Vehicle Routing: Applications.- Modeling.- Anticipatory.- Solution Approaches.- Literature Classification.- Part II: Shastic Customer Requests.- Motivation.- SDVRP with Shastic Requests.- Solution Algorithms.- Computational Evaluation.- Conclusion and Outlook.