Title: Optimisation inspiring from behaviour of raining in nature: droplet optimisation algorithm

Authors: Milad Yasrebi; Arash Eskandar-Baghban; Hamid Parvin; Majid Mohammadpour

Addresses: Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran ' Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran ' Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran; Young Researchers and Elite Club, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran ' Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran; Young Researchers and Elite Club, Yasuj Branch, Islamic Azad University, Yasuj, Iran

Abstract: In this paper, the droplet optimisation algorithm (DOA) has been proposed. DOA emulates rainfall phenomenon. It employs some special operators to describe the droplet process, including droplet generation, droplet fall, droplet collision, droplet flowing and droplet updating. To compare performance of this algorithm against those of some up-to-date optimisation algorithms, all of the CEC 2005 contest benchmark functions have been employed. The experimental results have proven that DOA is superior to all basic optimisation algorithms and also some up-to-date optimisation algorithms.

Keywords: optimiser; droplet optimisation algorithm; DOA; metaheuristics; general optimisation.

DOI: 10.1504/IJBIC.2018.094616

International Journal of Bio-Inspired Computation, 2018 Vol.12 No.3, pp.152 - 163

Accepted: 28 Dec 2016
Published online: 04 Sep 2018 *

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