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Multi-population Runge Kutta Optimizer Based on Gaussian Disturbance

Published: 16 August 2023 Publication History

Abstract

To address the lack of development capacity of Runge Kutta Optimizer, we propose the Multi-population Runge Kutta algorithm Based on Gaussian disturbance(MPRUN). In the algorithm, the population is divided into subgroups. The individuals in the subgroups are randomly selected for a global search with decreasing search radius with the number of iterations, which is used to improve the global search ability of the subgroups. In addition, the algorithm introduces a Gaussian disturbance mechanism to generate more uniformly distributed populations, performing random perturbation to the global best individual. Finally, the performance of the optimized algorithm is verified by 30 test set functions.

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YAN Shaoqiang, LIU Weidong, YANG Ping, WU Fengxuan, and YAN Zhe. Multi group sparrow search algorithm based on K-means clustering[J/OL]. Journal of Beijing University of Aeronautics and Astronautics:1-13[2023-03-28].https://doi.org/10.13700/j.bh.1001-5965.2022.0328.
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Xinchao Zhao, Ziyang Liu, and Xiangjun Yang. 2014. A multi-swarm cooperative multistage perturbation guiding particle swarm optimizer. Appl. Soft Comput. 22 (September, 2014), 77–93. https://doi.org/10.1016/j.asoc.2014.04.042
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Huiling, Chen., Shimin, Li., Ali, Asghar, Heidari., Ali, Asghar, Heidari., Pengjun, Wang., Jiawei, Li., Yutao, Yang., Mingjing, Wang., Changcheng, Huang. (2020). Efficient Multi-population Outpost Fruit Fly-driven Optimizers: Framework and Advances in Support Vector Machines. Expert Systems With Applications, 142:112999-.
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PRIS '23: Proceedings of the 2023 5th International Conference on Pattern Recognition and Intelligent Systems
July 2023
123 pages
ISBN:9781450399968
DOI:10.1145/3609703
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 August 2023

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  • the National Key Research and Development Program of China

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PRIS 2023

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