Chaotic Taboo Fish Algorithm for Traveling Salesman Problem
Aiming at the sensitivity of initial solution to the artificial fish algorithm, and the slowness of algorithm convergence speed, and the lowness of solution precision, according to the optimization improvement strategies of staging and variable parameter optimizing, and combined with the relevant rules taboo search algorithm, put forward a kind of improved chaotic taboo fish algorithm. The algorithm optimization process is divided into locking optimal solution or partial solution of the neighborhood and obtaining high-precision two-stage optimal solution, setting different parameters for each phase. And use the algorithm for solving the traveling salesman problem. Experimental results show that the algorithm convergence speed and high accuracy.
KeywordsArtificial fish algorithm chaos taboo search TSP problem
Unable to display preview. Download preview PDF.
- 1.Yang, W.-B., Zhao, Y.-W.: Improved simulated annealing algorithm for TSP. Computer Engineering and Applications 46(15), 34–36 (2010)Google Scholar
- 8.Li, X., Qian, J.: Studies on artificial fish swarm algorithm based on decomposition and coordination techniques. Journal of Circuits and Systems 8(1), 1–6 (2003) (in Chinese)Google Scholar
- 9.Li, X., Shao, Z., Qian, J.: An optimizing method based on autonomous animats: fish swarm algorithm. Practice and Theory for System Engineering 11, 32–38 (2002) (in Chinese)Google Scholar
- 11.Zhu, M.-H., She, X.-Y.: Improved artificial fish school algorithm to solve traveling salesman problem. Application Research of Computers 20(10), 3734–3736 (2010)Google Scholar
- 12.Qu, L.-D., He, D.-X.: Artificial Fish-School Algorithm Based on Adaptive Gauss Mutation. Computer Engineering 33(15), 182–184 (2009)Google Scholar