On the effectiveness of nature-inspired metaheuristic algorithms for performing phase equilibrium thermodynamic calculations.
The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheur...
| Publicado en: | Scientific World Journal pp. 374510 - 374511 |
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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=103831140&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103831140 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: 103831140 NLM24967430 2012629936 10.1155/2014/374510 NLM24967430 PMC4055435 103831140 ppf: 374510 ppct: 1 formats: tig: atl: On the effectiveness of nature-inspired metaheuristic algorithms for performing phase equilibrium thermodynamic calculations. aug: au: Fateen, Seif-Eddeen K Bonilla-Petriciolet, Adrian affil: Department of Chemical Engineering, Cairo University, Giza 12316, Egypt. sug: subj: Algorithms Models, Theoretical ab: The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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