系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2006年
3期
83~87
,共null页
资源均衡 Hopfield 模拟退火 权值状态发生器 增广置位矩阵
資源均衡 Hopfield 模擬退火 權值狀態髮生器 增廣置位矩陣
자원균형 Hopfield 모의퇴화 권치상태발생기 증엄치위구진
resource leveling; Hopfleld; simulated annealing; weight-state generator; augmented permute matrix
为有限资源均衡问题提供一个神经网络解决方法.首先提出增广置位矩阵,描述了资源均衡的神经网络表示,使得神经元的输出和问题的解彼此对应起来;然后在时间和资源约束下利用多种技巧构造网络的能量函数,使其能量最小值对应于资源最均衡的状态;并且提出基于“权值状态发生器”的离散Hopfield与模拟退火算法（DHNN-SA）融合的镶嵌式混合结构,从本质上提高了网络的优化质量;最后设计了资源优化神经网络的模拟程序.
為有限資源均衡問題提供一箇神經網絡解決方法.首先提齣增廣置位矩陣,描述瞭資源均衡的神經網絡錶示,使得神經元的輸齣和問題的解彼此對應起來;然後在時間和資源約束下利用多種技巧構造網絡的能量函數,使其能量最小值對應于資源最均衡的狀態;併且提齣基于“權值狀態髮生器”的離散Hopfield與模擬退火算法（DHNN-SA）融閤的鑲嵌式混閤結構,從本質上提高瞭網絡的優化質量;最後設計瞭資源優化神經網絡的模擬程序.
위유한자원균형문제제공일개신경망락해결방법.수선제출증엄치위구진,묘술료자원균형적신경망락표시,사득신경원적수출화문제적해피차대응기래;연후재시간화자원약속하이용다충기교구조망락적능량함수,사기능량최소치대응우자원최균형적상태;병차제출기우“권치상태발생기”적리산Hopfield여모의퇴화산법（DHNN-SA）융합적양감식혼합결구,종본질상제고료망락적우화질량;최후설계료자원우화신경망락적모의정서.
This paper provides a Neural Network solution for resource leveling problem. In order to give the neural network description of resource leveling problem and make the output eorrespondent with neurons, the new concept of Augmented permute matrix is proposed. Some novel technologies arc using when setting up the energy function under time and resources constrains. An Embedded Hybrid Model combining Discrete-time Hopfield model and SA （DHNNSA） is put forward to improve the optimization in essence in which Hopfield servers as State Generator for the SA. At last, the simulating program built on DHNN-SA is created. The results of the comparing with professional project management software show that the energy function and hybrid model given in this paper is highly efficient in solving resource leveling problem to some extent.
