Flower pollination algorithm for global optimization
Yang, Xin-She (2012) Flower pollination algorithm for global optimization. In: Unconventional Computation and Natural Computation: 11th International Conference, UCNC 2012, Orléan, France, September 3-7, 2012. Proceedings. Lecture Notes in Computer Science (7445). Springer, Berlin, pp. 240-249. ISBN 9783642328930
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Official URL: http://link.springer.com/chapter/10.1007%2F978-3-6...
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. (from publisher's website)
|Item Type:||Book Section|
|Keywords (uncontrolled):||Computation by Abstract Devices Algorithm Analysis and Problem Complexity Mathematical Logic and Formal Languages Artificial Intelligence (incl. Robotics) Logics and Meanings of Programs Computational Biology/Bioinformatics|
|Research Areas:||A. Middlesex University Schools and Centres > School of Science and Technology > Design Engineering and Mathematics|
|Deposited On:||21 Nov 2012 12:38|
|Last Modified:||25 Feb 2015 17:48|
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