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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
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