A global optimization method for nonconvex separable programming problems

doi:10.1016/S0377-2217(98)00243-4

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DC 欄位	值	語言
dc.contributor.author	Li, HL	en_US
dc.contributor.author	Yu, CS	en_US
dc.date.accessioned	2014-12-08T15:46:16Z	-
dc.date.available	2014-12-08T15:46:16Z	-
dc.date.issued	1999-09-01	en_US
dc.identifier.issn	0377-2217	en_US
dc.identifier.uri	http://dx.doi.org/10.1016/S0377-2217(98)00243-4	en_US
dc.identifier.uri	http://hdl.handle.net/11536/31124	-
dc.description.abstract	Conventional methods of solving nonconvex separable programming (NSP) problems by mixed integer programming methods requires adding numerous 0-1 variables. In this work, we present a new method of deriving the global optimum of a NSP program using less number of 0-1 variables. A separable function is initially expressed by a piecewise linear function with summation of absolute terms. Linearizing these absolute terms allows us to convert a NSP problem into a linearly mixed 0-1 program solvable for reaching a solution which is extremely close to the global optimum. (C) 1999 Elsevier Science B.V. All rights reserved.	en_US
dc.language.iso	en_US	en_US
dc.subject	goal programming	en_US
dc.subject	piecewise linear function	en_US
dc.subject	separable programming	en_US
dc.title	A global optimization method for nonconvex separable programming problems	en_US
dc.type	Article	en_US
dc.identifier.doi	10.1016/S0377-2217(98)00243-4	en_US
dc.identifier.journal	EUROPEAN JOURNAL OF OPERATIONAL RESEARCH	en_US
dc.citation.volume	117	en_US
dc.citation.issue	2	en_US
dc.citation.spage	275	en_US
dc.citation.epage	292	en_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.department	Department of Information Management and Finance	en_US
dc.identifier.wosnumber	WOS:000081318000007	-
dc.citation.woscount	15	-
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