The vehicle routing problem
Pickup and Delivery with Time Windows: Algorithms and Test Case Generation
ICTAI '01 Proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence
A Metaheuristic for the Pickup and Delivery Problem with Time Windows
ICTAI '01 Proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A set covering approach for the pickup and delivery problem with general constraints on each route
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
A job grouping approach for planning container transfers at automated seaport container terminals
Advanced Engineering Informatics
Dynamic pickup and delivery with transfers
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
Large neighborhood search for dial-a-ride problems
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Guided ejection search for the pickup and delivery problem with time windows
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
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
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This paper presents a two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows and multiple vehicles (PDPTW). The first stage uses a simple simulated annealing algorithm to decrease the number of routes, while the second stage uses Large neighborhood search (LNS) to decrease total travel cost. Experimental results show the effectiveness of the algorithm which has produced many new best solutions on problems with 100, 200, and 600 customers. In particular, it has improved 47% and 76% of the best solutions on the 200 and 600-customer benchmarks, sometimes by as much as 3 vehicles. These results further confirm the benefits of two-stage approaches in vehicle routing. They also answer positively the open issue in the original LNS paper, which advocated the use of LNS for the PDPTW and argue for the robustness of LNS with respect to side-constraints.