A review of Hopfield neural networks for solving mathematical programming problems
學年 98
學期 1
出版（發表）日期 2009-11-01
作品名稱 A review of Hopfield neural networks for solving mathematical programming problems
作品名稱（其他語言）
著者 Wena, Ue-Pyng; Lan, Kuen-Ming; Shih, Hsu-Shih
單位 淡江大學經營決策學系
出版者 Amsterdam: Elsevier BV * North-Holland
著錄名稱、卷期、頁數 European Journal of Operational Research 198(3), pp.675-687
摘要 The Hopfield neural network (HNN) is one major neural network (NN) for solving optimization or mathematical programming (MP) problems. The major advantage of HNN is in its structure can be realized on an electronic circuit, possibly on a VLSI (very large-scale integration) circuit, for an on-line solver with a parallel-distributed process. The structure of HNN utilizes three common methods, penalty functions, Lagrange multipliers, and primal and dual methods to construct an energy function. When the function reaches a steady state, an approximate solution of the problem is obtained. Under the classes of these methods, we further organize HNNs by three types of MP problems: linear, non-linear, and mixed-integer. The essentials of each method are also discussed in details. Some remarks for utilizing HNN and difficulties are then addressed for the benefit of successive investigations. Finally, conclusions are drawn and directions for future study are provided.
關鍵字 Hopfield neural networks;Energy function;Mathematical programming;penalty function;Lagrange multiplier;Primal and dual functions
語言 en
ISSN 0377-2217
期刊性質 國外
收錄於 SCI EI
產學合作
通訊作者 Shih, Hsu-Shih
審稿制度
國別 NLD
公開徵稿
出版型式 紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/27396 )

機構典藏連結
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