Flower Pollination Algorithm for Global Optimization

  • Xin-She Yang
Conference paper

DOI: 10.1007/978-3-642-32894-7_27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7445)
Cite this paper as:
Yang XS. (2012) Flower Pollination Algorithm for Global Optimization. In: Durand-Lose J., Jonoska N. (eds) Unconventional Computation and Natural Computation. UCNC 2012. Lecture Notes in Computer Science, vol 7445. Springer, Berlin, Heidelberg

Abstract

Flower pollination is an intriguing process in the natural world. Its evolutionary characteristics can be used to design new optimization algorithms. In this paper, we propose a new algorithm, namely, flower pollination algorithm, inspired by the pollination process of flowers. We first use ten test functions to validate the new algorithm, and compare its performance with genetic algorithms and particle swarm optimization. Our simulation results show the flower algorithm is more efficient than both GA and PSO. We also use the flower algorithm to solve a nonlinear design benchmark, which shows the convergence rate is almost exponential.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xin-She Yang
    • 1
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK

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