A global optimization method for nonconvex separable programming problems
| dc.citation.epage | 292 | en_US |
| dc.citation.issue | 2 | en_US |
| dc.citation.spage | 275 | en_US |
| dc.citation.volume | 117 | en_US |
| dc.citation.woscount | 15 | |
| dc.contributor.author | Li, HL | en_US |
| dc.contributor.author | Yu, CS | 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.date.accessioned | 2014-12-08T15:46:16Z | |
| dc.date.available | 2014-12-08T15:46:16Z | |
| dc.date.issued | 1999-09-01 | en_US |
| 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.identifier.doi | 10.1016/S0377-2217(98)00243-4 | en_US |
| dc.identifier.issn | 0377-2217 | en_US |
| dc.identifier.journal | EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1016/S0377-2217(98)00243-4 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/31124 | |
| dc.identifier.wosnumber | WOS:000081318000007 | |
| 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 |