教師資料查詢 | 類別: 期刊論文 | 教師: 時序時HSU-SHIH SHIH (瀏覽個人網頁)

標題:A neural network approach to multiobjective and multilevel programming problems
學年92
學期2
出版(發表)日期2004/07/01
作品名稱A neural network approach to multiobjective and multilevel programming problems
作品名稱(其他語言)
著者時序時; Shih, Hsu-shih; Wen, Ue-pyng; Lee, S.; Lan, Kuen-ming; Hsiao, Han-chyi
單位淡江大學經營決策學系
出版者Elsevier
著錄名稱、卷期、頁數Computers & Mathematics with Applications 48(1-2), pp.95-108
摘要This study aims at utilizing the dynamic behavior of artificial neural networks (ANNs) to solve multiobjective programming (MOP) and multilevel programming (MLP) problems. The traditional and non-traditional approaches to the MLP are first classified into five categories. Then, based on the approach proposed by Hopfield and Tank [1], the optimization problem is converted into a system of nonlinear differential equations through the use of an energy function and Lagrange multipliers. Finally, the procedure is extended to MOP and MLP problems. To solve the resulting differential equations, a steepest descent search technique is used. This proposed nontraditional algorithm is efficient for solving complex problems, and is especially useful for implementation on a large-scale VLSI, in which the MOP and MLP problems can be solved on a real time basis. To illustrate the approach, several numerical examples are solved and compared.
關鍵字Neural network;Energy function;Multilevel programming;Multiobjective programming;Dynamic behavior
語言英文
ISSN0898-1221
期刊性質國外
收錄於
產學合作
通訊作者
審稿制度
國別英國
公開徵稿
出版型式,紙本
相關連結
SDGs
  • 尊嚴就業與經濟發展,負責任的消費與生產,和平正義與有力的制度
Google+ 推薦功能,讓全世界都能看到您的推薦!