Optimisation inspiring from behaviour of raining in nature: droplet optimisation algorithm. (2018)

• Record Type: Journal Article
• Authors: Yasrebi, Milad; Eskandar-Baghban, Arash; Parvin, Hamid; Mohammadpour, Majid
• Is Part Of: International journal of bio-inspired computation. Volume 12:Number 3(2018)
• Page Start: 152
• Page End: 163
• Publication Date: 2018
• Subjects: optimiser -- droplet optimisation algorithm -- DOA -- metaheuristics -- general optimisation; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

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.