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:An Artificial Neural Network Approach to Multi-objective Programming and Multi-level Programming Problems
學年92
學期2
出版(發表)日期2004/07/01
作品名稱An Artificial Neural Network Approach to Multi-objective Programming and Multi-level Programming Problems
作品名稱(其他語言)
著者Shih, Hsu-Shih; Wen, Ue-Pyng; Lee, S.; Lan, Kuen-Ming; Hsiao, Han-Chyi
單位淡江大學管理科學學系
出版者Kidlington: Pergamon Press
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
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國別英國
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