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 en
ISSN 0898-1221
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度
國別 GBR
公開徵稿
出版型式 紙本
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