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A Scalable MapReduce-enabled Glowworm Swarm Optimization Approach for High Dimensional Multimodal Functions

Author

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  • Ibrahim Aljarah

    (Department of Business Information Technology, The University of Jordan, Amman, Jordan)

  • Simone A. Ludwig

    (Department of Computer Science, North Dakota State University, Fargo, ND, USA)

Abstract

Glowworm Swarm Optimization (GSO) is one of the common swarm intelligence algorithms, where GSO has the ability to optimize multimodal functions efficiently. In this paper, a parallel MapReduce-based GSO algorithm is proposed to speedup the GSO optimization process. The authors argue that GSO can be formulated based on the MapReduce parallel programming model quite naturally. In addition, they use higher dimensional multimodal benchmark functions for evaluating the proposed algorithm. The experimental results show that the proposed algorithm is appropriate for optimizing difficult multimodal functions with higher dimensions and achieving high peak capture rates. Furthermore, a scalability analysis shows that the proposed algorithm scales very well with increasing swarm sizes. In addition, an overhead of the Hadoop infrastructure is investigated to find if there is any relationship between the overhead, the swarm size, and number of nodes used.

Suggested Citation

  • Ibrahim Aljarah & Simone A. Ludwig, 2016. "A Scalable MapReduce-enabled Glowworm Swarm Optimization Approach for High Dimensional Multimodal Functions," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 7(1), pages 32-54, January.
    • Handle: RePEc:igg:jsir00:v:7:y:2016:i:1:p:32-54
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    Cited by:

    1. Shikha Agarwal & Prabhat Ranjan, 2018. "MR-TP-QFPSO: map reduce two phases quantum fuzzy PSO for feature selection," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(4), pages 888-900, August.

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