Earticle

초록

영어

In order to improve the search result and low evolution speed, and avoid the tendency towards stagnation and falling into the local optimum of ant colony optimization(ACO) in solving the complex function, the traditional ant colony optimization algorithm is analyzed in detail, an improved ant colony optimization(IWSMACO) algorithm based on information weight factor and supervisory mechanism is proposed in this paper. In the proposed IWSMACO algorithm, the information weight factor is added to the path selection and pheromone adjustment mechanisms in order to dynamically adjust path selection probability and randomly select the behavior rules for further intelligentializing the ant colony. The supervisory mechanism added the dynamic convergence criterion of supervisory distance and used the optimal pheromone update strategy to self-adaptively select the excellent ants for updating the pheromone trails, and improve the solution qualities of each iteration, better guide the later ants for learning. Finally, the proposed IWSMACO algorithm is carried out by 12 TSP instances. The simulation experiment results show that the proposed IWSMACO algorithm can not only avoid falling into the local optimum, but also enhance the convergence speed. And it takes on remarkable optimized ability and higher search accuracy.

목차

Abstract
 1. Introduction
 2. Traveling Salesmen Problem
 3. Ant Colony Optimization(ACO) Algorithm
 4. Improved ACO Algorithm Based on Information Weight Factor and Supervisory Mechanism
  4.1. The Information Weight Factor
  4.2. The Supervisory Mechanism
 5. TSP Numerical Experiment and Results Analysis
 6. Conclusion
 Acknowledgments
 References

키워드

저자

• Wenli Lei [ School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710072 China, School of Physics and Electronic Information, Yan’an University, Yan’an 716000 China ]
• Fubao Wang [ School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710072 China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605