Solving the Assignment Problem Using Continuous-Time and Discrete-Time Improved Dual Networks
Solving the Assignment Problem Using Continuous-Time and Discrete-Time Improved Dual Networks
复制标题
DOI：
10.1109/tnnls.2012.2187798
复制
发表时间：
2012-02
影响因子：
10.4
通讯作者：
Xiaolin Hu;Jun Wang
中科院分区：
文献类型：
--
作者：
Xiaolin Hu;Jun Wang
指派问题是一个典型的组合优化问题。在这个简短的，我们提出了一个连续时间版本和离散时间版本的改进的对偶神经网络（IDNN）解决分配问题。与文献中的大多数分配网络相比，这两个版本的IDNN由于其简单的结构而在电路实现上具有优势。理论上保证了这两种算法都全局收敛于指派问题的解，只要解是唯一的。
The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Both of them are theoretically guaranteed to be globally convergent to a solution of the assignment problem if only the solution is unique.