Fuzzy Discrete Particle Swarm Optimization for Solving Traveling Salesman Problem
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
International Journal of Bio-Inspired Computation
Hybrid dynamic k-nearest-neighbour and distance and attribute weighted method for classification
International Journal of Computer Applications in Technology
Design of wide-beam antenna using dynamic multi-objective BBO/DE
International Journal of Computer Applications in Technology
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The particle swarm optimisation (PSO) does well in the continuous optimisation problems. To solve travelling salesman problem (TSP) with the PSO, priority coding method is presented to code the solution of the TSP. Then a method based on dynamic setting of velocity range is proposed for the PSO to remove the side effect which results from inconsistency of the search space and the solution space under the priority coding method. The experiment shows: the descending velocity range could achieve this goal and the descending rate of velocity range should match up with that of the priority range in position vector. In addition, a new approach based on cluster analysis on the swarm with the k-centres method is proposed for preventing the PSO from local optimum during solving the TSP. Through this mechanism, the diversity of the swarm could be reserved as the computation goes on, which could improve the performance of the PSO.