http://repository.iitr.ac.in/handle/123456789/9901
Title: | A Survey on Parallel Particle Swarm Optimization Algorithms |
Authors: | Lalwani S. Sharma H. Satapathy S.C. Deep, K. Bansal J.C. |
Published in: | Arabian Journal for Science and Engineering |
Abstract: | Most of the complex research problems can be formulated as optimization problems. Emergence of big data technologies have also commenced the generation of complex optimization problems with large size. The high computational cost of these problems has rendered the development of optimization algorithms with parallelization. Particle swarm optimization (PSO) algorithm is one of the most popular swarm intelligence-based algorithm, which is enriched with robustness, simplicity and global search capabilities. However, one of the major hindrance with PSO is its susceptibility of getting entrapped in local optima and; alike other evolutionary algorithms the performance of PSO gets deteriorated as soon as the dimension of the problem increases. Hence, several efforts are made to enhance its performance that includes the parallelization of PSO. The basic architecture of PSO inherits a natural parallelism, and receptiveness of fast processing machines has made this task pretty convenient. Therefore, parallelized PSO (PPSO) has emerged as a well-accepted algorithm by the research community. Several studies have been performed on parallelizing PSO algorithm so far. Proposed work presents a comprehensive and systematic survey of the studies on PPSO algorithms and variants along with their parallelization strategies and applications. © 2019, King Fahd University of Petroleum & Minerals. |
Citation: | Arabian Journal for Science and Engineering (2019), 44(4): 2899-2923 |
URI: | https://doi.org/10.1007/s13369-018-03713-6 http://repository.iitr.ac.in/handle/123456789/9901 |
Issue Date: | 2019 |
Publisher: | Springer Verlag |
Keywords: | GPU Large-size complex optimization problems MPI Parallel computing Particle swarm optimization Swarm intelligence-based algorithm |
ISSN: | 2193567X |
Author Scopus IDs: | 55772632500 56229215400 16643664100 8561208900 57189656835 |
Author Affiliations: | Lalwani, S., Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India Sharma, H., Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India Satapathy, S.C., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India Deep, K., Department of Mathematics, Indian Institute of Technology, Roorkee, India Bansal, J.C., South Asian University, New Delhi, India |
Funding Details: | Acknowledgements The first author (S.L.) gratefully acknowledges Science & Engineering Research Board, DST, Government of India, for the fellowship (PDF/2016/000008). |
Corresponding Author: | Lalwani, S.; Department of Computer Science and Engineering, Rajasthan Technical UniversityIndia; email: slalwani.math@gmail.com |
Appears in Collections: | Journal Publications [MA] |
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