Quaternionic flower pollination algorithm

2Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Metaheuristic-based optimization techniques offer an elegant and easy-to-follow framework to optimize different types of problems, ranging from aerodynamics to machine learning. Though such techniques are suitable for global optimization, they can still be get trapped locally under certain conditions, thus leading to reduced performance. In this work, we propose a quaternionic-based Flower Pollination Algorithm (FPA), which extends standard FPA to possibly smoother search spaces based on hypercomplex representations. We show the proposed approach is more accurate than five other metaheuristic techniques in four benchmarking functions. We also present a parallel version of the proposed approach that runs much faster.

Cite

CITATION STYLE

APA

Rosa, G. H., Afonso, L. C. S., Baldassin, A., Papa, J. P., & Yang, X. S. (2017). Quaternionic flower pollination algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10425 LNCS, pp. 47–58). Springer Verlag. https://doi.org/10.1007/978-3-319-64698-5_5

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free