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Social Strategy of Particles in Optimization Problems

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Optimization of Complex Systems: Theory, Models, Algorithms and Applications (WCGO 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 991))

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Abstract

The article presents a particle swarm optimization algorithm (SoPSO) in which a novel effective acceleration coefficient has been proposed. In the presented approach, the proposed acceleration coefficient is a nonlinear function that depends on the performance of the algorithm and is affected by a number of iterations. This strategy allows to more precisely specify the search direction and better control velocity of the algorithm according to which it travels in the search space to discover the best, optimal solution of the considered problem. The presented strategy was examined on the collection of benchmark functions described in the literature. The test results were compared with those achieved by the improved IPSO algorithm and the standard PSO (SPSO).

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Author information

Authors and Affiliations

  1. Institute of Information Technology, Lodz University of Technology, Wólczańska 215, 90-924, Lodz, Poland

    Bożena Borowska

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  1. Bożena Borowska
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Correspondence to Bożena Borowska .

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Editors and Affiliations

  1. Computer science and Applications Department, LGIPM, University of Lorraine, Metz Cedex 03, France

    Hoai An Le Thi

  2. Computer Science and Applications Department, LGIPM, University of Lorraine, Metz Cedex 03, France

    Hoai Minh Le

  3. Laboratory of Mathematics, National Institute for Applied Sciences (INSA)-Rouen Normadie, Saint-Étienne-du-Rouvray Cedex, France

    Tao Pham Dinh

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Borowska, B. (2020). Social Strategy of Particles in Optimization Problems. In: Le Thi, H., Le, H., Pham Dinh, T. (eds) Optimization of Complex Systems: Theory, Models, Algorithms and Applications. WCGO 2019. Advances in Intelligent Systems and Computing, vol 991. Springer, Cham. https://doi.org/10.1007/978-3-030-21803-4_54

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