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Table of Contents
Intro
Preface
Organization of the Book
Audience
Contents
List of Contributors
Acronyms
1 New Advances in Vehicle Routing Problems: A Literature Review to Explore the Future
1.1 Introduction
1.2 Electric Vehicle Routing Problem
1.2.1 Refueling Policy
1.2.1.1 Full Charging Policy
1.2.1.2 Partial Charging Policy
1.2.1.3 Battery Swapping
1.2.2 Energy Consumption Rate
1.2.3 Fleet Size and Mix
1.3 Green Vehicle Routing Problem
1.3.1 Transportation and Energy Consumption
1.3.2 The Pollution-Routing Problem
1.4 Hybrid Vehicle Routing Problem
1.5 Conclusions
1.5.1 Future Research Directions in EVRP
1.5.2 Future Research Directions in GVRP
1.5.3 Future Research Directions in HVRP
References
2 A Robust Optimization for a Home Healthcare Routing and Scheduling Problem Considering Greenhouse Gas Emissions and Stochastic Travel and Service Times
2.1 Introduction
2.2 Literature Review
2.3 Problem Definition
2.3.1 Assumptions
2.3.2 Deterministic Model
2.3.3 Robust Optimization Version
2.4 Proposed Solution
2.4.1 Encoding Plan
2.4.2 Multi-Objective of KA (MOKA)
2.4.2.1 Primary Procedure
2.4.2.2 Attraction and Swirling
2.4.2.3 Replace the Members of N2 Set with New Ones
2.4.2.4 Move the Member of N3 Set
2.4.2.5 Stopping Condition
2.5 Experimental Results
2.5.1 Instances
2.5.2 Tuning
2.5.3 Comparison
2.6 Conclusion and Future Works
References
3 A Skewed General Variable Neighborhood Search Approach for Solving the Battery Swap Station Location-Routing Problem with Capacitated Electric Vehicles
3.1 Introduction
3.2 Problem Definition
3.3 Solution Approach
3.3.1 Local Search
3.3.1.1 Neighborhood Structures
3.3.1.2 Seq-VND
3.3.1.3 Mixed-VND
3.3.2 Skewed General Variable Neighborhood Search Algorithm (SGVNS)
3.4 Experimental Results
3.5 Conclusion
References
4 The Cumulative Capacitated Vehicle Routing Problem Including Priority Indexes
4.1 Introduction
4.2 Literature Review
4.3 Problem Description
4.4 Mathematical Formulation
4.4.1 Reformulation Using Epsilon Constraint
4.5 Metaheuristic Algorithm
4.5.1 Non-dominated Sorting Genetic Algorithm
4.5.1.1 Constructive Procedure
4.5.1.2 Crossover Procedure/Mechanism
4.5.1.3 Mutation Procedure/Mechanism
4.5.2 Particle Swarm Optimization Algorithm
4.6 Computational Experience
4.6.1 Set of Instances and Parameters Tunning
4.6.2 Experimental Results for the Solved Instances
4.6.3 Experimental Results for Larger Instances
4.7 Conclusions and Future Work
References
5 Solution of a Real-Life Vehicle Routing Problem with Meal Breaks and Shifts
5.1 Introduction
5.2 Literature Review
5.3 Mathematical Model
5.4 The Proposed Heuristic TPH
5.4.1 Initial Solution Generation
5.4.2 Local Search
5.4.3 Route Elimination
5.4.3.1 RelocationForRouteKilling
Preface
Organization of the Book
Audience
Contents
List of Contributors
Acronyms
1 New Advances in Vehicle Routing Problems: A Literature Review to Explore the Future
1.1 Introduction
1.2 Electric Vehicle Routing Problem
1.2.1 Refueling Policy
1.2.1.1 Full Charging Policy
1.2.1.2 Partial Charging Policy
1.2.1.3 Battery Swapping
1.2.2 Energy Consumption Rate
1.2.3 Fleet Size and Mix
1.3 Green Vehicle Routing Problem
1.3.1 Transportation and Energy Consumption
1.3.2 The Pollution-Routing Problem
1.4 Hybrid Vehicle Routing Problem
1.5 Conclusions
1.5.1 Future Research Directions in EVRP
1.5.2 Future Research Directions in GVRP
1.5.3 Future Research Directions in HVRP
References
2 A Robust Optimization for a Home Healthcare Routing and Scheduling Problem Considering Greenhouse Gas Emissions and Stochastic Travel and Service Times
2.1 Introduction
2.2 Literature Review
2.3 Problem Definition
2.3.1 Assumptions
2.3.2 Deterministic Model
2.3.3 Robust Optimization Version
2.4 Proposed Solution
2.4.1 Encoding Plan
2.4.2 Multi-Objective of KA (MOKA)
2.4.2.1 Primary Procedure
2.4.2.2 Attraction and Swirling
2.4.2.3 Replace the Members of N2 Set with New Ones
2.4.2.4 Move the Member of N3 Set
2.4.2.5 Stopping Condition
2.5 Experimental Results
2.5.1 Instances
2.5.2 Tuning
2.5.3 Comparison
2.6 Conclusion and Future Works
References
3 A Skewed General Variable Neighborhood Search Approach for Solving the Battery Swap Station Location-Routing Problem with Capacitated Electric Vehicles
3.1 Introduction
3.2 Problem Definition
3.3 Solution Approach
3.3.1 Local Search
3.3.1.1 Neighborhood Structures
3.3.1.2 Seq-VND
3.3.1.3 Mixed-VND
3.3.2 Skewed General Variable Neighborhood Search Algorithm (SGVNS)
3.4 Experimental Results
3.5 Conclusion
References
4 The Cumulative Capacitated Vehicle Routing Problem Including Priority Indexes
4.1 Introduction
4.2 Literature Review
4.3 Problem Description
4.4 Mathematical Formulation
4.4.1 Reformulation Using Epsilon Constraint
4.5 Metaheuristic Algorithm
4.5.1 Non-dominated Sorting Genetic Algorithm
4.5.1.1 Constructive Procedure
4.5.1.2 Crossover Procedure/Mechanism
4.5.1.3 Mutation Procedure/Mechanism
4.5.2 Particle Swarm Optimization Algorithm
4.6 Computational Experience
4.6.1 Set of Instances and Parameters Tunning
4.6.2 Experimental Results for the Solved Instances
4.6.3 Experimental Results for Larger Instances
4.7 Conclusions and Future Work
References
5 Solution of a Real-Life Vehicle Routing Problem with Meal Breaks and Shifts
5.1 Introduction
5.2 Literature Review
5.3 Mathematical Model
5.4 The Proposed Heuristic TPH
5.4.1 Initial Solution Generation
5.4.2 Local Search
5.4.3 Route Elimination
5.4.3.1 RelocationForRouteKilling