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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/10419
Title: Novel inertia weight strategies for particle swarm optimization
Authors: Chauhan P.
Deep, K.
Pant M.
Published in: Memetic Computing
Abstract: The performance of PSO algorithm depends greatly on the appropriate parameter selection strategies for fine tuning its parameters. This paper proposes three new nonlinear strategies for selecting inertia weight which plays a significant role in particle's foraging behaviour. The PSO variants implying these strategies are named as: fine grained inertia weight PSO (FGIWPSO); Double Exponential Self Adaptive IWPSO (DESIWPSO) and Double Exponential Dynamic IWPSO (DEDIWPSO). In FGIWPSO, inertia weight is obtained adaptively, depending on particle's iteration wise performance and decreases exponentially. DESIWPSO and DEDIWPSO employ Gompertz function, a double exponential function for selecting inertia weight. In DESIWPSO the particles' iteration wise performance is fed as input to the Gompertz function. On the other hand DEDIWPSO evaluates the inertia weight for whole swarm iteratively using Gompertz function where relative iteration is fed as input. The efficacy and efficiency of proposed approaches is validated on a suite of benchmark functions. The proposed variants are compared with non linear inertia weight and exponential inertia weight strategies. Experimental results assert that the proposed modifications help in improving PSO performance in terms of solution quality as well as convergence rate. © 2013 Springer-Verlag Berlin Heidelberg.
Citation: Memetic Computing (2013), 5(3): 229-251
URI: https://doi.org/10.1007/s12293-013-0111-9
http://repository.iitr.ac.in/handle/123456789/10419
Issue Date: 2013
Keywords: convergence
Dynamic inertia weight
Fine grained inertia weight
Particle swarm optimization
Stagnation
ISSN: 18659284
Author Scopus IDs: 35752990300
8561208900
23467551900
Author Affiliations: Chauhan, P., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667 Uttarakhand, India
Deep, K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667 Uttarakhand, India
Pant, M., Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, 247667 Uttarakhand, India
Funding Details: Acknowledgments This work was financially supported by Ministry of Human Resources, New Delhi, India
Corresponding Author: Chauhan, P.; Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667 Uttarakhand, India; email: pinkeychauhan030@gmail.com
Appears in Collections:Journal Publications [MA]

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