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

Yasrebi, Milad; Eskandar-Baghban, Arash; Parvïn, Hamïd; Mohammadpour, Majid

doi:10.1504/ijbic.2018.10015866

Cited by 2 publications

(2 citation statements)

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“…The last waterbased metaheuristic introduced in the literature is the Droplet Optimization Algorithm (DOA), which was published at the end of 2018 in [18]. Although in this case the metaphor is not so clear as in previous metaheuristics, the method gets inspiration from the droplet generation in clouds, the droplet descent from clouds to the ground, and the evaporation.…”

Section: Doa: Droplet Optimization Algorithmmentioning

confidence: 99%

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Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

Rubio

Rodrı́guez

2019

Complexity

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Many water-based optimization metaheuristics have been introduced during the last decade, both for combinatorial and for continuous optimization. Despite the strong similarities of these methods in terms of their underlying natural metaphors (most of them emulate, in some way or another, how drops collaboratively form paths down to the sea), in general the resulting algorithms are quite different in terms of their searching approach or their solution construction approach. For instance, each entity may represent a solution by itself or, alternatively, entities may construct solutions by modifying the landscape while moving. A researcher or practitioner could assume that the degree of similarity between two water-based metaheuristics heavily depends on the similarity of the natural water mechanics they emulate, but this is not the case. In order to bring some clarity to this mosaic of apparently related metaheuristics, in this paper we introduce them, explain their mechanics, and highlight their differences.

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Section: Doa: Droplet Optimization Algorithmmentioning

confidence: 99%

“…Thus, it has only been used by its creators. In fact, only one paper (see [18]) has been published dealing with DOA, and all the examples presented in it belong to a standard benchmark used at the CEC Conference.…”

Section: Doa: Droplet Optimization Algorithmmentioning

confidence: 99%