Approximate Dynamic Programming for Dynamic Vehicle Routing.

• Format: Electronic eBook
• Language: English
• Published: Springer Verlag 2017.
• Series: Operations research/computer science interfaces series ; 61.
• Subjects: Vehicle routing problem.; Transportation, Automotive > Dispatching.; Dynamic programming.; elektronické knihy; electronic books
• ISBN: 9783319555119; 9783319555102
• ISSN: 1387-666X ;
• Physical Description: 1 online resource

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 lookin...

Table of Contents:

• Foreword; Acknowledgements; About this Book; Contents; Acronyms; List of Figures; List of Tables; Algorithms; 1 Introduction; 1.1 Prescriptive Analytics; 1.2 Scope of This Work; 1.3 Outline of the Following Chapters; 1.4 A Recipe for ADP in SDVRPs; 1.4.1 The Application; 1.4.2 The Model; 1.4.3 Anticipatory Approaches; Part I Dynamic Vehicle Routing; 2 Rich Vehicle Routing: Environment; 2.1 Vehicle Routing; 2.2 RVPR: Characteristics and Definition; 2.3 RVRPs in Logistics Management; 2.4 RVRPs in Hierarchical Decision Making; 2.5 Recent Developments of the RVRP-Environment.
• 2.5.1 E-Commerce and Globalization2.5.2 Urbanization and Demography; 2.5.3 Urban Environment and Municipal Regulations; 2.5.4 Technology; 2.5.5 Data and Forecasting; 2.6 Implications; 3 Rich Vehicle Routing: Applications; 3.1 General RVRP-Entities; 3.1.1 Infrastructure; 3.1.2 Vehicles; 3.1.3 Customers; 3.2 Plans; 3.3 Objectives; 3.3.1 Costs; 3.3.2 Reliability; 3.3.3 Objective Measures; 3.4 Constraints; 3.4.1 Time Windows; 3.4.2 Working Hours; 3.4.3 Capacities; 3.5 Drivers of Uncertainty; 3.5.1 Travel Times; 3.5.2 Service Times; 3.5.3 Demands; 3.5.4 Requests; 3.6 Classification.
• 3.7 Service Vehicles3.8 Transportation Vehicles; 3.8.1 Passenger Transportation; 3.8.2 Transportation of Goods; 3.9 Implications; 3.9.1 Decision Support; 3.9.2 Modeling of Planning Situations; 3.9.3 Modeling of Uncertainty; 3.9.4 Modeling of Subsequent Planning; 3.9.5 Modeling of Applications; 3.9.6 Modeling of Anticipation; 3.9.7 Anticipatory Methods; 4 Modeling; 4.1 Stochastic Dynamic Decision Problem; 4.1.1 Dynamic Decision Problems; 4.2 Markov Decision Process; 4.2.1 Definition; 4.2.2 Decision Policies and Problem Realizations; 4.3 Stochastic Dynamic Vehicle Routing.
• 4.4 Modeling Planning Situations4.4.1 Decision State; 4.4.2 Decision Making; 4.5 Modeling Uncertainty; 4.5.1 Deterministic Modeling; 4.5.2 Travel Time; 4.5.3 Service Time; 4.5.4 Demands; 4.5.5 Requests; 4.5.6 Stochastic Transitions in SDVRPs; 4.6 Modeling SDVRPs as MDPs; 4.6.1 Decision Points; 4.6.2 Travel Times; 4.6.3 Service Times; 4.6.4 Demands; 4.6.5 Requests; 4.7 Vehicle Routing with Recourse Actions; 4.8 Route-Based Markov Decision Process; 4.9 Implications; 4.9.1 Properties of SDVRP; 4.9.2 Definition, Reconstruction, and Simulation; 4.9.3 Anticipation and Prescriptive Analytics.
• 5 Anticipation5.1 Definition; 5.2 Anticipation in SDVRPs; 5.3 Perfect Anticipation; 5.3.1 Optimal Policies; 5.3.2 Derivation of Optimal Policies; 5.3.3 Limitations; 5.4 Classification of Anticipation; 5.4.1 Reactive Versus Non-reactive; 5.4.2 Implicit, Explicit, and Perfect; 5.4.3 Focus of Anticipation: Offline and Online; 5.5 Reactive Explicit Anticipation; 6 Anticipatory Solution Approaches; 6.1 Non-reactive Anticipation; 6.1.1 Non-reactive Implicit Anticipation; 6.1.2 Non-reactive Explicit Anticipation; 6.2 Reactive Anticipation; 6.2.1 Reactive Implicit Anticipation.