Abstract
This paper exposes a new hybrid approach based on Ant Colony Optimization heuristics, Route First-Cluster Second methods and Local search procedures, combined to generate high quality solutions for the Vehicle Routing Problem. This method uses the parallel computing power of modern general purpose GPUs and multicore CPUs, outperforming current ACO-based VRP solvers and showing to be a competitive approach compared to other high performing metaheuristic solvers.
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CITATION STYLE
Rey, A., Prieto, M., Gómez, J. I., Tenllado, C., & Hidalgo, J. I. (2018). A CPU-GPU Parallel Ant Colony Optimization Solver for the Vehicle Routing Problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10784 LNCS, pp. 653–667). Springer Verlag. https://doi.org/10.1007/978-3-319-77538-8_44
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