Abstract
Constrained function optimization using particle swarm optimization (PSO) with polynomial mutation is proposed in this work. In this method non-stationary penalty function approach is adopted and polynomial mutation is performed on global best solution in PSO. The proposed method is applied on 6 benchmark problems and obtained results are compared with the results obtained from basic PSO. The experimental results show the efficiency and effectiveness of the method.
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Si, T., Jana, N.D., Sil, J. (2011). Constrained Function Optimization Using PSO with Polynomial Mutation. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_26
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DOI: https://doi.org/10.1007/978-3-642-27172-4_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27171-7
Online ISBN: 978-3-642-27172-4
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