The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems.
This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in cora...
| Publicado en: | Scientific World Journal pp. 739768 - 739769 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109676333&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109676333 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109676333 109676333 NLM25147860 2012693829 10.1155/2014/739768 NLM25147860 PMC4132328 109676333 ppf: 739768 ppct: 1 formats: tig: atl: The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems. aug: au: Salcedo-Sanz, S Del Ser, J Landa-Torres, I Gil-López, S Portilla-Figueras, J A sug: subj: Models, Biological Algorithms Ecosystem Invertebrates Physiology Models, Theoretical Animal Studies Comparative Studies Multicenter Studies Evaluation Research Validation Studies ab: This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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