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dc.contributor.authorLu, Hao-Chunen_US
dc.contributor.authorLi, Han-Linen_US
dc.contributor.authorGounaris, Chrysanthos E.en_US
dc.contributor.authorFloudas, Christodoulos A.en_US
dc.date.accessioned2014-12-08T15:07:43Z-
dc.date.available2014-12-08T15:07:43Z-
dc.date.issued2010-01-01en_US
dc.identifier.issn0925-5001en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s10898-009-9414-2en_US
dc.identifier.urihttp://hdl.handle.net/11536/6072-
dc.description.abstractConvex underestimation techniques for nonlinear functions are an essential part of global optimization. These techniques usually involve the addition of new variables and constraints. In the case of posynomial functions x(1)(alpha 1)x(2)(alpha 2) ... x(n)(alpha n), logarithmic transformations (Maranas and Floudas, Comput. Chem. Eng. 21: 351-370, 1997) are typically used. This study develops an effective method for finding a tight relaxation of a posynomial function by introducing variables y(j) and positive parameters beta(j), for all alpha(j) > 0, such that y(j) = x(j)(-beta j). By specifying beta(j) carefully, we can find a tighter underestimation than the current methods.en_US
dc.language.isoen_USen_US
dc.subjectConvex underestimationen_US
dc.subjectPosynomial functionsen_US
dc.titleConvex relaxation for solving posynomial programsen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s10898-009-9414-2en_US
dc.identifier.journalJOURNAL OF GLOBAL OPTIMIZATIONen_US
dc.citation.volume46en_US
dc.citation.issue1en_US
dc.citation.spage147en_US
dc.citation.epage154en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000272375600010-
dc.citation.woscount9-
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