Name
Abstract | ||
|---|---|---|
Over the past few decades numerous attemptshave been made to solve combinatorial optimizationproblems that are NP-complete or NP-hardin heuristic approach. A Hopfield-type neuralnetwork is a method that is often used to solveproblems such as Traveling Salesman Problem.However, it is difficult to find an optimal solutionbecause it is based on gradient descent and itsenergy function has many local minima. Therefore,many attempts have been made to find waysof escaping from local minima... |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/KES.1999.820237 | KES |
Keywords | Field | DocType |
computational complexity,local minima,traveling salesman problem,neural networks,np hard problems,tabu search,gradient descent,recurrent neural networks,np complete problems,intelligent networks,optimization problem,intelligent systems | Hill climbing,Mathematical optimization,Heuristic,Gradient descent,Computer science,Recurrent neural network,Maxima and minima,Travelling salesman problem,Optimization problem,Tabu search | Conference |
Citations | PageRank | References |
1 | 0.35 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J Konishi | 1 | 17 | 4.50 |
| S. Shimba | 2 | 1 | 0.35 |
| Jun Toyama | 3 | 130 | 19.87 |
| Mineichi Kudo | 4 | 927 | 116.09 |
| Masaru Shimbo | 5 | 179 | 33.02 |