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research-article

Modified particle swarm optimization for multimodal functions and its application

Authors:

Neetu Kushwaha,

Millie PantAuthors Info & Claims

Volume 78, Issue 17

Pages 23917 - 23947

https://doi.org/10.1007/s11042-018-6324-7

Published: 01 September 2019 Publication History

Abstract

In this paper, a Modified variant of Particle Swarm Optimization named MPSOPR is proposed. The velocity update in MPSOPR follows a neighbourhood-based learning strategy based on PageRank (PR) algorithm and a scale-free network is proposed for the interaction among particles in the population. This is in contrast to the basic PSO which has a fully connected topology or regular topology. The inclusion of these two modifications helps in enhancing the diversity and the information dissemination ability of the algorithm. Performance of MPSOPR is validated on a set of 17 benchmark problems divided into 3 groups, on basis of level of difficulties. Comparative analysis of the results obtained through MPSOPR with 9 other variants of PSO, indicate that the proposed scheme can help in improving the performance of PSO significantly. The performance of MPSOPR is further validated by employing it for solving problems related to recommender system.

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Cited By

Pawan YPrakash KChowdhury SHu Y(2022)Particle swarm optimization performance improvement using deep learning techniquesMultimedia Tools and Applications10.1007/s11042-022-12966-181:19(27949-27968)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s11042-022-12966-1
Dutta PSaha SNaskar S(2021)A multi-objective based PSO approach for inferring pathway activity utilizing protein interactionsMultimedia Tools and Applications10.1007/s11042-020-09269-880:20(30283-30303)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s11042-020-09269-8

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Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 78, Issue 17

Sep 2019

1379 pages

ISSN:1380-7501

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Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

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Kluwer Academic Publishers

United States

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Published: 01 September 2019

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Cited By

Pawan YPrakash KChowdhury SHu Y(2022)Particle swarm optimization performance improvement using deep learning techniquesMultimedia Tools and Applications10.1007/s11042-022-12966-181:19(27949-27968)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s11042-022-12966-1
Dutta PSaha SNaskar S(2021)A multi-objective based PSO approach for inferring pathway activity utilizing protein interactionsMultimedia Tools and Applications10.1007/s11042-020-09269-880:20(30283-30303)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s11042-020-09269-8

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