Name
Abstract | ||
|---|---|---|
To compensate for the shortcomings of existing methods used in TSP (Traveling Salesman Problem), such as the accuracy of solutions and the scale of problems, this paper proposed an improved particle swarm optimization by using a self-organizing construction mechanism and dynamic programming algorithm. Particles are connected in way of scale-free fully informed network topology map. Then dynamic programming algorithm is applied to realize the evolution and information exchange of particles. Simulation results show that the proposed method with good stability can effectively reduce the error rate and improve the solution precision while maintaining a low computational complexity. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.7148/2013-0862 | PROCEEDINGS 27TH EUROPEAN CONFERENCE ON MODELLING AND SIMULATION ECMS 2013 |
Keywords | Field | DocType |
Particle swarm algorithm, dynamic programming algorithm, scale-free fully informed network, travelling salesman problem | Particle swarm optimization,Bottleneck traveling salesman problem,Mathematical optimization,Computer science,Multi-swarm optimization,Travelling salesman problem,2-opt,Metaheuristic | Conference |
Citations | PageRank | References |
1 | 0.41 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinli Xu | 1 | 79 | 10.92 |
| Xu Cheng | 2 | 1 | 0.41 |
| Zhong-Chen Yang | 3 | 1 | 0.41 |
| Xuhua Yang | 4 | 13 | 7.04 |
| Wan-Liang Wang | 5 | 235 | 39.16 |