The vehicle routing problem
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
INFORMS Journal on Computing
Very large-scale vehicle routing: new test problems, algorithms, and results
Computers and Operations Research
A cooperative parallel meta-heuristic for the vehicle routing problem with time windows
Computers and Operations Research
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
Computers and Operations Research
Active-guided evolution strategies for large-scale capacitated vehicle routing problems
Computers and Operations Research
Fifty Years of Vehicle Routing
Transportation Science
A Parallel Algorithm for the Vehicle Routing Problem
INFORMS Journal on Computing
A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems
Operations Research
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This paper introduces a cooperative parallel metaheuristic for the capacitated vehicle routing problem. The proposed metaheuristic consists of multiple parallel tabu search threads that cooperate by asynchronously exchanging best-found solutions through a common solution pool. The solutions sent to the pool are clustered according to their similarities. The search history information identified from the solution clusters is applied to guide the intensification or diversification of the tabu search threads. Computational experiments on two sets of large-scale benchmark instance sets from the literature demonstrate that the suggested metaheuristic is highly competitive, providing new best solutions to ten of those well-studied instances.