Overview
- 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
- Includes supplementary material: sn.pub/extras
Part of the book series: Operations Research/Computer Science Interfaces Series (ORCS, volume 61)
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Table of contents (12 chapters)
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Front Matter
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Dynamic Vehicle Routing
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Front Matter
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Stochastic Customer Requests
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Front Matter
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Back Matter
Keywords
About this book
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.
Authors and Affiliations
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, Stochastic Optimization, and Approximate Dynamic Programming.
Bibliographic Information
Book Title: Approximate Dynamic Programming for Dynamic Vehicle Routing
Authors: Marlin Wolf Ulmer
Series Title: Operations Research/Computer Science Interfaces Series
DOI: https://doi.org/10.1007/978-3-319-55511-9
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-55510-2Published: 27 April 2017
Softcover ISBN: 978-3-319-85681-0Published: 09 May 2018
eBook ISBN: 978-3-319-55511-9Published: 19 April 2017
Series ISSN: 1387-666X
Series E-ISSN: 2698-5489
Edition Number: 1
Number of Pages: XXV, 197
Number of Illustrations: 49 b/w illustrations, 6 illustrations in colour
Topics: Operations Research/Decision Theory, Operations Research, Management Science