| dc.contributor | 資科系 | |
| dc.creator (作者) | Huang, T. L.;Hwang, T.Y.;Chang, C.H.;Sheu, J.S.;wang, C.T.;Lien, Y.N.;Huang, C.C.;Chen, C.R. | |
| dc.creator (作者) | 連耀南 | zh_TW |
| dc.date (日期) | 2010 | |
| dc.date.accessioned | 21-Dec-2015 16:01:56 (UTC+8) | - |
| dc.date.available | 21-Dec-2015 16:01:56 (UTC+8) | - |
| dc.date.issued (上傳時間) | 21-Dec-2015 16:01:56 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/79692 | - |
| dc.description.abstract (摘要) | The purpose of this paper is to address the multi-objective optimization via combined fuzzy satisfied method and evolution programming (E.P.) method. The concept of non-inferiority is employed to characterize a solution of the multi-objective problem. Then, a fuzzy satisfied method based on evolutionary programming is introduce d to determine the optimal solution. As a result, the objective functions of the optimization problem are modeled with fuzzy sets to represent their imprecise natur e. That also enables us to reduce the inaccuracies in decision-makers` judgments. A time-sharing computer program is implemented, and an application to a multi-objective operation problem in feeder reconfiguration in electric power systems is demonstrated along with the computer outputs. In conclusion, the proposed solution algorithm allows for a more realistic problem formulation efficiently obtained the optimal solution for the tested system with a large search space. | |
| dc.format.extent | 129 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Journal of Information and Optimization Sciences, 31(6), 1263-1274 | |
| dc.title (題名) | Multi-objective optimization via fuzzy-evolution method | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1080/02522667.2010.10700026 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1080/02522667.2010.10700026 | |
