The vehicle routing problem
Using Constraint-Based Operators to Solve the Vehicle Routing Problem with Time Windows
Journal of Heuristics
Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
Algorithms for a temporal decoupling problem in multi-agent planning
Eighteenth national conference on Artificial intelligence
Constraint Processing
A Reactive Variable Neighborhood Search for the Vehicle-Routing Problem with Time Windows
INFORMS Journal on Computing
A cooperative parallel meta-heuristic for the vehicle routing problem with time windows
Computers and Operations Research
A Guided Cooperative Search for the Vehicle Routing Problem with Time Windows
IEEE Intelligent Systems
Active guided evolution strategies for large-scale vehicle routing problems with time windows
Computers and Operations Research
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
Transportation Science
HM '08 Proceedings of the 5th International Workshop on Hybrid Metaheuristics
Per-Seat, On-Demand Air Transportation Part II: Parallel Local Search
Transportation Science
A concurrent evolutionary approach for rich combinatorial optimization
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Randomized adaptive spatial decoupling for large-scale vehicle routing with time windows
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows
Computers and Operations Research
Arc-guided evolutionary algorithm for the vehicle routing problem with time windows
IEEE Transactions on Evolutionary Computation
A two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows
Computers and Operations Research
Large neighborhood search and adaptive randomized decompositions for flexible jobshop scheduling
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Randomized adaptive vehicle decomposition for large-scale power restoration
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Computers and Operations Research
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositions which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions.