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Power Mutation Embedded Modified PSO for Global Optimization Problems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6466))

Abstract

In the present study we propose a simple and modified framework for Particle Swarm Optimization (PSO) algorithm by incorporating in it a newly defined operator based on Power Mutation (PM). The resulting PSO variants are named as (Modified Power Mutation PSO) MPMPSO and MPMPSO 1 which differs from each other in the manner of implementation of mutation operator. In MPMPSO, PM is applied stochastically in conjugation with basic position update equation of PSO and in MPMPSO 1, PM is applied on the worst particle of swarm at each iteration. A suite of ten standard benchmark problems is employed to evaluate the performance of the proposed variations. Experimental results show that the proposed MPMPSO outperforms the existing method on most of the test functions in terms of convergence and solution quality.

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Chauhan, P., Deep, K., Pant, M. (2010). Power Mutation Embedded Modified PSO for Global Optimization Problems. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17563-3_17

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  • DOI: https://doi.org/10.1007/978-3-642-17563-3_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17562-6

  • Online ISBN: 978-3-642-17563-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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