Please use this identifier to cite or link to this item:
https://lib.hpu.edu.vn/handle/123456789/34467
Title: | A New Optimization Based on Parallelizing Hybrid PSOGSA Algorithm |
Authors: | Yu, Jie Wang, Hong Jiang Pan, Jeng Shyang Chang, Kuo Chi Ngô, Trường Giang Nguyễn, Trọng Thể |
Keywords: | Parallel PSOGSA algorithm Mutation strategy Particle swarm optimization Gravitational search algorithm |
Issue Date: | 2021 |
Publisher: | Springer |
Abstract: | This study suggests a new metaheuristic algorithm for global optimization, based on parallel hybridizing the swarm optimization(PSO) andGravitational search algorithm (GSA). Subgroups of the population are formed by dividing the swarm’s community. Communication between the subsets can be developed by adding strategies for the mutation. Twenty-three benchmark functions are used to test its performance to verify the feasibility of the proposed algorithm. Compared with the PSO, GSA, and parallel PSO (PPSO), the findings of the proposed algorithm reveal that the proposed PPSOGSA achieves higher precision than other competitor algorithms. |
URI: | https://lib.hpu.edu.vn/handle/123456789/34467 |
Appears in Collections: | Bài báo khoa học |
Files in This Item:
File | Description | Size | Format | |
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A-New-Optimization-Based-on-Parallelizing-Hybrid-PSOGSA-Algorithm_Nguyen-Trong-The.pdf Restricted Access | 548.78 kB | Adobe PDF | View/Open Request a copy |
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