Earticle

초록

영어

In order to improve the global solving ability and convergence speed, avoid falling into local optimal solution, the basic ant colony optimization (ACO) algorithm is improved to propose an efficient and intelligent ant colony optimization (IMVPACO)algorithm. In the IMVPACO algorithm, the updating rules and adaptive adjustment strategy of pheromones are modify in order to better reflect the quality of the solution based on the increment of pheromone. The dynamic evaporation factor strategy is used to achieve the better balance between the solving efficiency and solving quality, and effectively avoid falling into local optimum for quickening the convergence speed. The movement rules of the ants are modify to make it adaptable for large-scale problem solving, optimize the path and improve search efficiency. A boundary symmetric mutation strategy is used to obtain the symmetric mutation for iteration results, which not only strengthens the mutation efficiency, but also improves the mutation quality. Finally, the proposed IMVPACO algorithm is applied in solving the traveling salesman problem. The simulation experiments show that the proposed IMVPACO algorithm can obtain very good results in finding optimal solution. And It takes on better global search ability and convergence performance than other traditional methods.

목차

Abstract
 1. Introduction
 2. Basic Ant Colony Optimization Algorithm
 3. Improved Ant Volony Optimization (IMVPACO) Algorithm
  3.1. Dynamic Movement Rules of Ants
  3.2. Improved Updating Rules of Pheromone
  3.3. Adaptive Adjustment Strategy of Pheromone
  3.4. Dynamic Evaporation Factor Strategy
  3.5. Boundary Symmetric Mutation Strategy
 4. The Steps of the Proposed IMVPACO Algorithm
 5. Experimental Analysis
  5.1. Experiment Introduction and Parameter Set
  5.2. Experimental Results and Analysis
 6. Conclusion
 References

키워드

저자

• Ping Duan [ Department of Information Engineering, Hubei Urban Construction Vocational and Technological College, Wuhan 430205 China ]
• Yong AI [ Department of Information Engineering, Hubei Urban Construction Vocational and Technological College, Wuhan 430205 China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605