Abstract
In this paper, we present a novel approach named “ACO-PSO-TSP-GPU” to run PSO and ACO on Graphical Processing Units (GPUs) and applied to TSP (Parallel-PSO&ACO-A-TSP). Both algorithms are implemented on GPUs. Well-known benchmark problems for many heuristic and meta heuristic algorithms presented by Travelling Salesman Problem (TSP) are known as NP hard complex problems.TSP was investigated using classical approaches as well as intelligent techniques employing Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). Parallel computing is well suited to the execution of nature and bio-inspired algorithms due to the rapidity of parallel implementation. Results show better performance optimization when using parallelism compared to results using sequential CPU implementation.
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Acknowledgments
The authors would like to acknowledge the financial support of this work by grants from General Direction of Scientific Research (DGRST), Tunisia, under the ARUB program.
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Bali, O., Elloumi, W., Abraham, A., Alimi, A.M. (2017). ACO-PSO Optimization for Solving TSP Problem with GPU Acceleration. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_55
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DOI: https://doi.org/10.1007/978-3-319-53480-0_55
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