期刊論文
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 ) |