Name
Title | ||
|---|---|---|
A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem |
Abstract | ||
|---|---|---|
•A novel NN-based hybrid method for solving quadratic-BLPPs is presented.•Proposed algorithm combines GA (handles upper-level problem) and DRNN (for lower-level decision problem).•GA solves the upper-level decision problem by choosing candidate solutions and passing them to the lower-level.•Parameterized dual-NN is used in the lower-level problem to determine the optimal solutions.•This combination offers many benefits like parallel computing, faster convergence to global optimum, etc. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2020.04.013 | Neurocomputing |
Keywords | DocType | Volume |
Quadratic Bi-Level Programming Problem (BLPP),Recurrent Neural Networks (RNN),Genetic Algorithm (GA),Hybrid Strategy, | Journal | 407 |
ISSN | Citations | PageRank |
0925-2312 | 1 | 0.37 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junzo Watada | 1 | 411 | 84.53 |
| Arunava Roy | 2 | 1 | 0.37 |
| Jingru Li | 3 | 1 | 0.37 |
| Bo Wang | 4 | 224 | 53.43 |
| Shuming Wang | 5 | 229 | 15.96 |