BSP-GA: A new Genetic Algorithm for System Optimization and Excellent Schema Selection.
The significance of Internet-of-Things to Supply Chain Management has been dramatically increasing. The performance of supply chain based on Internet-of-Things is largely dependent on its optimization. Genetic algorithms (GAs) are important intelligent methods for complex system optimization problem...
| Publicado en: | Systems Research & Behavioral Science Vol. 31; no. 3; pp. 337 - 353 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Wiley-Blackwell
May/Jun2014
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=96200836&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 96200836 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10927026 2SN jtl: Systems Research & Behavioral Science issn: 10927026 maglogo: Y pubinfo: dt: May/Jun2014 vid: 31 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 96200836 10.1002/sres.2280 ppf: 337 ppct: 16 formats: tig: atl: BSP-GA: A new Genetic Algorithm for System Optimization and Excellent Schema Selection. aug: au: Jin, Chenxia Li, Fachao Wilamowska ‐ Korsak, Marzana Li, Ling Fu, Liuliu affil: School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang China Safety Engineering Department, College of Engineering, Warmia and Mazury University at Olsztyn, Olsztyn Poland Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk VA, USA Tsinghua University, Beijing China su: Technology Decision making Genetic algorithms Internet of things Global optimization Supply chains sug: subj: Technology Decision making Genetic algorithms Internet of things Global optimization Supply chains keyword: excellent schema genetic algorithms (GA) global optimization Internet ‐ of ‐ Things (IoT) Internet-of-Things (IoT) schema theory excellent schema genetic algorithms (GA) global optimization Internet ‐ of ‐ Things (IoT) Internet-of-Things (IoT) schema theory ab: The significance of Internet-of-Things to Supply Chain Management has been dramatically increasing. The performance of supply chain based on Internet-of-Things is largely dependent on its optimization. Genetic algorithms (GAs) are important intelligent methods for complex system optimization problems, but they have some internal drawbacks such as premature and slow convergence to the global optimum. In this paper, we present a new schema protection based GA (BSP-GA). First, we propose three principles for selecting excellent schema based on the schema theory; second, we propose the concept of K-intensive effect synthesis operator, and we give a general five-intensive effect synthesis operator and its proof; third, we give the selection process of excellent schema through an example, and further we give the implementation steps of BSP-GA. The performance of BSP-GA has been compared with simple GA by using two carefully chosen benchmark problems. It has been observed that BSP-GA can yield the global optimum more efficiently than commonly used simple GA. Furthermore, a theorem is presented to guarantee the convergence of BSP-GA. Copyright © 2014 John Wiley & Sons, Ltd. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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